EPAM Systems, Inc. — Call Transcript 2026

Good morning, everyone. Thank you for joining us today. I'm Mike Rowshandel, Head of Investor Relations. Whether you're joining us live here in Boston or dialed in through the webcast, we appreciate you joining us today. We've been planning and preparing for this day for quite some time now, and I can tell you the energy in the backstage is buzzing. Our entire leadership team is here, eager to take you inside our story, what we've built over the past three decades, and more importantly, the how and why we're positioned to be successful in the AI era. Here's the thing: saying we're positioned to win is easy. Showing you is what today is all about. That brings me to our theme for the day, AI Made Real. Through today's presentations, you'll hear real client testimonials, providing a deep sense of the unique value we continue to deliver each and every day. Before we begin, I would like to remind that today's presentation contains forward-looking statements which are subject to risk and uncertainties. Please refer to the safe harbor statement in our presentation materials and SEC filings for a discussion of factors that could cause actual results to differ. We'll also reference certain non-GAAP financial measures. Reconciliations to the most comparable GAAP measures can be found in the appendix of today's presentation. Now let me walk you through what to expect over the next few hours. First, some context. Our last major update was nearly four years ago, and to say a lot has changed would be an understatement. The macro, geopolitics, competitive dynamics, AI disruption, the evolution of IT services, and EPAM itself all look very different than back then. That's why a key objective of today's presentation is to provide important clarity on where we are today and where we're headed over the next few years. Let me quickly walk you through the agenda. The day is organized into two parts. In the first section, we'll provide an important update on our strategy, how we're transforming our go-to-market motions, and then we'll dive into a key AI section where we'll talk about AI native engineering and AI native business transformation. In the second section, we'll focus on our engineering DNA, our AI talent, global delivery engine, and then we'll have an engaging panel discussion with several of our geographic leaders. We'll then dive into our financial imperatives and then finally close with a Q&A session. Finally, for those that have joined us live here in Boston, we invite you to please stick around after our main presentation. There's a highly interactive hour of client-led demonstrations and industry-led tours. These client demos and tours should give you a real sense of the AI capabilities we're delivering today. With that said, let's get kicked off with a quick video. With that, I would like to warmly welcome our Chief Executive Officer and President, Balazs Fejes, or better known as FB. Thank you. Mike, thank you very much. Good morning, good afternoon, good evening, everybody. Thanks for joining us here in Boston at our 2026 Investor and Analyst Day. My name is Balazs Fejes, just please call me FB. I'm not going to force you to learn how to pronounce Hungarian names. Mike probably spent two hours practicing how to pronounce it. You don't have to go through that. In the next probably 20 minutes, I would like to give you a strategic overview of EPAM, the market itself, how we are positioning ourselves to win in the AI native era. The first most important thing for me is that you have four things to take away from here. We are reinventing ourselves as a global leader in the AI transformation services space. We are leveraging industry's best engineering talent in the industry so as to solve our clients' hardest, most complex business and technology problems. We are strengthening our internal and client-facing AI capabilities to capitalize on the global AI transformation, and we are executing a clear strategy to drive our next phase of profitable growth. Before we start, I think we need to really address the elephant in the room. We are reading the same headlines, same Substacks. I think watching the same Instagram, TikTok, YouTube Shorts, or YouTube videos. Even just today there are some new news popping out from everywhere. It tells a story. It tells a story that AI capabilities are growing really, really fast. This is true, but this is only one side of the story. It only talks about AI capabilities growth, but it's not talking about the adoption rate in our societies and in our enterprise. These two are very different. Whereas AI capabilities are growing really fast, the adoption rate, the way people are changing how work gets done is growing much, much slower. There's a gap between those, and this gap is the opportunity for EPAM. EPAM is operating on the AI frontier. We transitioned into the AI frontier, and today we're going to show you how we've done that and how we're planning to stay there. How are we going to help our clients catch up to us using the learnings that we gained in the last three years? This is the opportunity of our lifetime. Just a month ago, we were talking to most of you and updated you on our 2025 results, delivering almost a $5.456 billion revenue. This is our sixth consecutive quarterly revenue growth on reported basis, and we are really proud of it. We are delivering across 55 countries with 62,000 EPAMers with 56,000 delivery professionals. It took us 30 years to get here. We have been around, we've seen a lot. In 2025, we really delivered this growth across all the industries, across all the different geographies with a wide and very distributed presence. We don't have real concentration on this. We feel it's very important given the current economics and current situation. But let me remind you who we are. EPAM, we are a build and change organization. In the last 30 years, that's what we've done. We honed our engineering heritage to actually build solutions for our clients. We are builders. We are delivering results relentlessly to our clients, helping them to navigate technology, geopolitical, and economic changes with our hybrid teams. That's who we are, and that's, I think, it's very important because we just entered the age of building. We are seeing that AI enables us to build new solutions, and that's our advantage, and that's our heritage. We are serving a diverse and global client list across 11 industries. 345 of our clients are part of Forbes Global 2000. 64 out of 100 are part of S&P 500 and the Global 2000 at the same time. The top 20 clients of ours on average had 13 years of tenure. We have deep relationships. 80+ of our top 100 clients are executing AI native projects with us. Actually, we're delivering for them new transformation projects. At the same time, we're winning new opportunities, we're winning new deals, and expanding our wallet share. We are positioned to harness the value of AI internally and also to capitalize on the growth opportunities, and I think that's very important as a key takeaway for us. Already in 2025, our results are benefited from AI. We delivered a very strong AI native and AI foundation momentum, which was built on five different foundations or pillars. We helped our client close the adoption gap with our skilled talent capabilities. We helped them optimize their delivery using AI SDLC, which we later on launched as part of AI/RUN. We helped them modernize their legacy system using AI, where we launched MFLens, which is a modernization toolkit. We also help our clients adopt physics AI and robotics. At the same time, we're helping clients globally to roll out sovereign AI, which is becoming more and more important in our increasingly more complex geopolitical space where we are operating in. TAM is very, very complex, and I'm sure all of you guys came here to understand how do we see TAM. Myself and not EPAM, we don't have a crystal ball. We just don't have that. We decided to borrow one from Gartner, I think. I'm going to use Gartner's crystal ball to try to explain to you where the market is going. Gartner predicts that the total market of IT services is going to grow to $1.8 trillion by 2029, which is a 5% CAGR. We are operating in a sub-segment, traditionally delivering solutions in business consulting, technology consulting, application implementation. This part of the segment is expected to go at 6.5% CAGR. It's a growing market and continues to grow. At the same time, we took another report, also from Gartner, which presented a very different picture. This really talks about the AI market itself. They are predicting that the total market of AI by 2029 will grow to $4.7 trillion. That includes all the GPUs, all the data center investments people need to make in order to make it work, and the software and the AI services too. The AI services part, which we are really looking, is we comprise multiple sectors, and we actually took just one slice of it, what we call AI services plus AI cybersecurity. It's a very fast-growing sector. It's actually growing by double-digit CAGR, sometimes strong or very strong double-digit CAGR till 2029. Now, what's important to take away is that the or Gartner's definition, what's AI services, and our definition of AI native doesn't really match because they do include some parts, which is what we call AI-assisted revenue. But still, very important takeaway, it's a fast-growing segment of the market. Now, I'm not going to be able to square off what's going to be replaced by AI or how much IT services is going to be impacted by itself, because nobody can, and we don't have the data for that. I'm just using this as information to demonstrate to you that it's a vast growing market which we're trying to tackle. On the other hand, I would like to really focus on why we are positioned ideally to win in this $1.3 trillion opportunity, which we call our AI services. EPAM has a client zero mentality. We spent three years building our capabilities, honing our capabilities, how to harness the power of AI on ourselves. This gives us credibility. We have an engineering heritage, and in the age of building and actually applying AI, it's a very difficult thing to do, and you need real engineering power and you need engineering capabilities to make it really work. We understand how to manage talent, how to create the next generation talent, which is so important in the next couple of years. We have deep industry expertise because without in-industry expertise, you don't know what to automate, you don't know what to change and how to really take advantage of AI. The only thing you keep talking about is how to take cost out, and that has a limit. We have long-standing client relationships, clients who trust us, and you're going to see demonstrations of that to actually experiment with them, how to use and how to roll out AI using our expertise, what we gained in the last three years internally. We have an aspiration. Our aspiration is we wanna become the go-to partner for enterprises for AI transformation, which is built on 3 strategic pillars. Number 1, we wanna position and establish EPAM as a leading software engineering services provider. We wanna transform ourselves to be an AI native organization, and we want to launch new AI native offerings, which we're going to talk about. The key enablers to make this happen is talent skills, which we talked about, strategic partnership, extending strategic partnerships, which we just very recently entered a partnership with Cursor, which is a very important part of the puzzle, domain and vertical expertise, and continuous investments into internal products, internal IP. We have been accelerating our internal transformation. We are true to our values of being a client zero. We spent three years implementing and changing how to run our business, how to run recruitment, project staffing, talent management, how we can do management reporting and finance and legal using AI. We got some recognition due to that in best use of AI or the best competence and skills development using AI. We have been recognized for this effort. Using all the knowledge what we gained in the last three years, back in autumn last year, we launched a codified go-to-market strategy under the brand name AI/RUN, which really addresses how to do AI native software engineering and how to do business transformation, which become an AI innovation-based business transformation. This consists of playbooks, blueprints, how to manage talent, and also tools, platforms behind it. This is based on real credible evidence, based on the three-year experiments which we're doing on ourselves. We're going to demonstrate it to you if you are in person in Boston with all the different shows around you. Also later today, we're going to actually show you how we implemented this tooling into our internal systems. We're creating new AI native business models and services. These are net new services, net new revenue for EPAM. These services are agentic intelligent operations, AI native experiences. Just a couple of months ago, we launched Empathy Lab in North America, which is our AI native services, experiences launch, and brand name under this. AI native agentic operations and agentic factories and agentic security. We are doubling down on our growth drivers, talent, skills and capabilities. Extending on our 30 years of heritage, Sandra and Alexei will be updating you how we are creating the new talent, how we creating the new roadmap to actually create the new talent, and how we're sensing who has the capability to get there. We are verticalizing and actually deepening our industry experience. We are pushing our consultancy teams into our verticalized industries. We're building, continue to build out internal platforms and IT assets, and of course, strategic partnerships where we need to strengthen, and we will double down our footprint. I think if you were following us in the last years, you heard a lot about our TelescopeAI. We invested decades in developing an enterprise backbone, digital backbone, which allowed us to manage our organization, manage us through crisis, manage us through different disruption, and continue allowing us to deliver with high quality. Now, we actually put an agentic backbone on top of it, which allows us, our teams and agents to interact with each other and actually take real-time data to drive better decision-making with higher quality output. Our leadership team has changed. We realigned our leadership structure around industries, brought in new members. You have the chance to interact with them throughout today. Some of them is going to come on stage and present, but this is the team who is going to take us to the next level. Why invest in EPAM? We are the best positioned growth leader for enterprise AI transformation. Our AI native and foundational work is expanding, driving significant growth in markets. We are the strongest solution builders in the industry with proven track record of solving our clients' most complex problems. We have a clear strategy. We are focused on accelerating organic growth while driving margin expansion. Let's dive into the details. I would like to invite Elaina Shekhter, our Chief Strategy & Transformation Officer, on stage and to tell us how to transform our go-to-market. Thank you very much. Thank you, FB. Good morning, everyone. I'm Elaina Shekhter, and as of two weeks ago, I'm the Chief Strategy and Transformation Officer. Before that, I was the Chief Marketing Officer, but today we have our brand-new Chief Marketing Officer here. Encourage everyone to meet Phil Walsh, who's gonna be walking around. Today, I wanna talk to you about what we're doing to transform our go-to-market approach. Over the years, EPAM has been particularly interested and really honestly obsessed with building the right kind of supply and addressing our customer needs in an overwhelming demand environment. Over the last few years, we've been investing significantly in our go-to-market approach and the transformation of all of our selling motions. Today, sorry for the clicker. Three key takeaways. We are transforming everything in the company. As FB just shared, our digital platforms, our talent ecosystem, how we think about delivery, everything is being built around an AI native blueprint. The same is true with our go-to-market approach. We are responding to an AI-centric environment with changing everything that we do in order to more effectively meet our customers where they are. That means that we're building domain and vertical expertise into every motion. Every sales engagement, every capability is driven around deep knowledge of our customers and their domains. We're adapting the way we go to market through our programs that address customer reach to our engagement and commercial models, and we're doing it in sync with, or sometimes ahead of, emerging industry trends. EPAM predominantly serves the enterprise. We've been doing so for years, and although we have a significant footprint in ISVs and helping high tech and software companies build, they themselves are large enterprises. Our primary segment today are large companies, and their service needs, and their landscape of service needs has changed significantly with the rise of AI, and it has never been more complex. Between market conditions that demand the addressing new competition, rising customer expectations, and all of the AI hype, all the technology trends which are constantly shifting on a daily basis, and our demand to meet expectations for advancing the transformations with AI, and the demands of the enterprises themselves, which are shifting also on a daily basis, demanding more strategy, more growth, better optimization programs, and overall better performance, and of course, a better use of capital, we are operating in a more complex enterprise environment than ever before. The market demands more flexibility, more capability, and more results delivered more relentlessly than ever before. To address these changing conditions, we are elevating our entire game and our go-to-market strategy with three key motions. Number one, we're shifting and extending our focus from building geographic capability to building full-scale capabilities. Think about a full stack of capabilities that includes domain, vertical, and effectively forward deploying those capabilities to our client engagements. Secondly, we're integrating a consultative approach around the whole of the go-to-market strategy. No more is it consulting over here, engineering over there. Our goal with our go-to-market transformation is to bridge strategy and execution, and in doing so, create a consulting moat in addition to the engineering moat, which my colleagues will be talking about right after this. We're accelerating our motions, starting with partnerships, but not only. We are changing the way we address the market in total, direct-to-client motions, sales and marketing transformation, and of course, the work that we do continuously with our partners. What this means for us is that we are future-proofing an organization by creating a forward momentum that's bringing capabilities to clients to meet them where they are today. Our evolving focus areas are necessarily about value creation. At the mention of our hybrid teams, we have a long-standing history of building hybrid engineering teams. Today, our job for our customers is to build high-velocity performance teams that include consultants and engineers. We are prioritizing developing critical industry-specific skills. This could be vertical. This could be horizontal. We're doing that not only around AI, we're doing it with AI. More on this to come. Finally, we're creating a global delivery value creation network that's optimized not just across locations, and Larry will talk more about that, but also around specific services and skills and capabilities of individual people and high-performing teams. Part of this integration is not only to build consulting into everything that we do, but it's actually to open EPAM up to alternative and additional buyers in order to capture new market share. Earlier this year, we announced the expansion of Empathy Lab into North America, having had a very successful launch last year in Europe. Empathy is our AI native agency, and it offers choice to CMOs who increasingly have their own budgets for technology, and yes, also AI, to engage with an EPAM that is ready to meet them where they are in driving key transformation programs in a way that is not encumbered by traditional agency dynamics. We also continue to invest and integrate a EPAM Continuum, which is our consulting brand, and the changes there are material. We are upgrading the entire consultancy workflow with and around AI. In doing so, we're expanding our addressable market, and we believe not only are we serving our existing clients better, but we're expanding our opportunities to attract and build new client relationships. EPAM has always been known as a technology solutions expert. This is everything we've been doing for the past 30 years. Across all three brands and across all of our front doors, we're adopting and adapting our solutions proposition around AI. By integrating consulting, what we can deliver is end-to-end enterprise-grade scaled solutions in the absolute most complex environments. For those of you who are staying with us for the afternoon, as you walk around the space, you'll see just how complex complexity is. We're driving consulting to be in lockstep with technology, and in doing so, we can guide our clients on where and how AI should be used. We're helping to determine not only the right technology platforms, but the right operating models. We're identifying critical constraints and blockers around compliance, governance, security, very material, especially these days. We're actually starting to run AI native work streams and business models end to end. This is part of our engagement model transformation. We believe we are the absolute best partner to scale solutions around AI and build for the future in the most complex enterprise environments. What about how we sell? To reach as many clients as possible with the most relevant propositions, we are transforming our full stack of sales and marketing motions in 2026. Everything that we've been doing for the last several years has been quote unquote digital. We were focused exclusively on driving optimization, modernization, and AI foundational work streams, and this continues today. In 2026, our value proposition includes the full digitization mix, but it is also driving optimization and agentic operations into both the growth agenda and the optimization agenda of our enterprise clients. How we manage sales is changing from account relationship management focus to really creating a hybrid seller, someone who is a forward deployed relationship manager who is at once a consultant, an engineer, and a relationship manager. We are adapting our pricing models. Of course, much of our business continues to be very much focused around T&M as much of the foundational work we continue to do is built around high-performance teams. But we're adding output-based, ROI-based, and business outcome-based models to our engagement mix successfully. Our sales cycle is changing from a more linear, sort of traditional sales cycle to one that is continuous. This is definitely a work in progress, and it will continue to evolve very quickly as we introduce agentic motions into both the top and the middle and the bottom of the funnel. Finally, marketing is transforming, and I'm very happy about that. From sequential brand through funnel activities, we are introducing a performance optimized marketing motion. With Phil on board, we're gonna be sharing a lot more with you on what that looks like. Beyond investing, we are transforming our sales motions and our approach to market in order to capture additional market share. Nowhere is this more evident in the acceleration of our partnering motions. We've been making announcements over the last few months, and there will be many more to come, and quite quickly I might add. Today, our ecosystem of partners includes over 160 different partners. These include the platforms, AI native players, industry partners, universities, research labs, and such. This ecosystem is constantly being built out and adjusted to suit our solutions and consulting propositions. With our partners, our motion has changed from partner-centric channel motion to one that accelerates our propositions and our value to clients. We are elevating our market sensing capabilities and helping our partners do the same through very much tailored, dedicated, and often IP-based campaigns that we're bringing to market as we speak. We're also, in some cases, working with our partners to help them build their own platforms, and in doing so, driving delivery efficiency and effectiveness for their own build-out operations. These are some of the partners we work with today. FB mentioned Cursor. There's many more obviously, and there's now a number of very interesting ones that are coming up, particularly around the area of security. Over the last months, we've announced these are just really a subset of the things that we've announced, and so the point here is our relationships with our partners go way beyond credentials. We are pushing the edge of AI innovation, and we're doing that with our partners and with our clients. You're seeing us show up in market with AI wins, with being named the AI innovation partner for some of the largest CSPs, with announcing agents into multiple marketplaces. This work continues and will be built on as part of our evolving go-to-market strategy. I wanna leave you with three ideas. One, we are very serious about transforming our go-to-market approach. We understand that the environment has shifted into an AI-centric environment, and we are there for it. Number two, we believe domain and vertical expertise is a critical success factor, and it is creating not only an engineering moat for us, but also a consulting moat and positioning EPAM to win in an incredibly complex market. Finally, we are innovating and amplifying our partnership motions together with over 160 of the world's leading companies. We're using that to adapt our models, everything that we do, from how we deliver to how we engage with our clients. Of course, we're EPAM, so we're starting with the software development life cycle and the product development cycle. It gives me great pleasure to welcome my colleagues, Dmitry Tovpeko, who is our VP of AI Engineering, and Adam Auerbach, who's our VP and Head of AI Enablement, to the stage to tell you more. Thank you. Good morning, everyone. My name is Dmitry Tovpeko. I lead AI engineering. My name is Adam Auerbach. I'm head of AI enablement. Adam and I are gonna walk you through what is changing in how software gets built and why does it matter for EPAM business. Boris Cherny, the creator of Claude Code, one of the most advanced AI tools in the market, in the recent interview famously said that coding is largely solved with AI. If that's true, why do clients still need EPAM? We believe there are four reasons for that. First, enterprise complexity is growing, and the demand for complex engineering is infinite. Second, AI demands a new type of engineering discipline that is difficult to master, and engineering depth is our moat. Third, we are agentic platform builders, not just users or adopters. We are codifying delivery, and we are scaling a new type of engineering profile to run it. Fourth, what you build for clients today becomes the foundation for autonomous enterprise AI that they will require tomorrow, and every engagement brings us closer. Now let's talk about the first point, the first dimension, which is enterprise complexity. Our clients operate across eight simultaneous complexity dimensions, and each one of them get new requirements with AI. Strategy and economics. All of the client businesses are disrupted. They are discussing what they should be doing and how they should be transforming their primary core products. In addition to technology and product transformations they need to run internally. Data foundation. Your agents are as good as your data, and your enterprise data is not ready for AI. Vendor strategy is a good one. Everybody's talking about which tools to select, but conversations also shifted to existing SaaS applications that are currently part of everybody's portfolio, and now clients are discussing whether they should retain them or they should rebuild these capabilities with AI. That creates a new set of questions and a new stream of engineering work. Every single dimension is getting new requirements. It is getting more and more complicated, and clients need a lot of help here. This is even before we talk about the changes that happens inside of software delivery and software engineering itself. Let's talk about it. When AI generates the code, the hard part becomes how do you create a system that generates it right. It all starts from design. Somebody needs to encode their specifications. What should go inside of them? All the domain knowledge, all the business workflows, all of these, proprietary knowledge in undocumented systems that is sitting inside of people's heads, all of that need to go there. Somebody need to architect the system. It is never a single agent that can do the work. This is always a complex agentic ecosystem that is ever-evolving and ever getting more and more complicated. Somebody needs to validate the output. Somebody need to judge. We see that the same tools produce very different results depending on engineers who are dealing with these tools, and the gap is getting wider. Finally, you need to connect these agentic ecosystems to your enterprise environments. With all of these established legacy ways of working, delivery pipelines, ecosystems, tools, integrations, all of that, and none of that was designed for AI, and now we need to deal with that. That creates a huge complexity inside of software engineering, which now is getting a new AI engineering discipline that didn't exist 12 months ago, to create AI engineering layer that can run the agents that are doing the work. This is exactly what we have done at EPAM. We codified the agentic system, the entire delivery pipeline with agents. I'm not talking about agents augmentation. That was easy part, so this is gone. What we are doing, we are creating a brand new, from the ground up, AI native ways of working that we codified in a repeatable pipeline, and that's the blueprint. Now, the blueprint is an easy part. The hard part is how you can actually scale it. In order to run it, you need a new type of engineer to deal with that. Traditional, narrow, specialized software engineers are actually not good in benefiting from these kind of blueprints. They can get maybe 10%, maybe 15%, but all of these stories about 2x, 3x, they require a very different profile. Somebody who can own engineering tasks end to end across all stages of SDLC, across multiple technology stacks, and this is where it is becoming very complicated. They need to be fluent in new AI tooling. They should be using them in very different ways. They should be able to judge whether the outputs at every step in the way are what they should be. This is what we call full stack agentic engineer profile, and scaling this profile is the hard part. Alexei and Sandra later today are gonna talk in more details about it. The question is, can anyone do this? We believe there are two things that are required to operate this at scale, and most companies cannot assemble both. First, you've got to have strong engineering culture and depth. This is not an upskilling program. This is not a scaled certification exercise for particular skill set. You have to start from the very high point from the very beginning. You have to have that as a part of your DNA already in order to be able to run in this race. We set these high standards many years ago, and now, 30 more years later, we are starting from a much higher point than many. Second, you've got to have delivery volume. You have to be able to run this pipeline against real enterprises over and over again, and this is where blueprint are getting battle tested. This is where they are becoming real. This is where you are facing real legacy problems. This is where they are becoming scalable, and they can bring value to our clients. Why we think most firms cannot assemble both? Of course, arbitrage firms, their model was optimized for narrow specialized engineer. Low rates, low complexity work, and they require particular profile to make it a profitable business, and we believe that these firms are exposed. EPAM hasn't been ever really playing a role there. We approach it differently. Strategy firms, they have intellectual depth, but they don't have muscle on the ground to make it real, to actually deliver on these promises. Product companies, they have engineering culture, they have great products, but they're only integrating with the enterprises. They're not working from within inside of this complexity. EPAM has both. We have the engineering culture, and we have the volume, and that's the mode. We believe that AI gets it wider. This only comes from doing the work. You are as good as your delivery. In AI, the right way to build reveals itself only through doing. No one figured it out from a whiteboard. All the great founders right now of AI tools, they're all hands-on. They all have a ton of experience. This is what we have built, and this is why we believe it is hard to replicate. Now Adam is going to walk you through how we are scaling this across our clients. Adam. Thank you, Dima. What Dima is describing to you is what we call level three maturity. What we have found is that there are multiple levels to this journey, and most people start at level one. Level one is they have access to Copilot, Cursor, a code assist tool, but no one really uses that tool. If you buy a tool, doesn't mean that people are going to use it. People need coaching. They need training. They need support. What they ultimately will find out is that that tool optimizes one aspect of development, coding. Yes, does it create efficiencies for developers? Sure. As Dima just said, there's much more to the software development life cycle than just writing code, and that's why you also need agents, and that's what level two is. Level two is this combination of a code assist tool with agents to help accelerate your current ways of working. That's the next challenge. Yes, level two will create the efficiencies that people are expecting with AI, faster cycle time, higher quality, better productivity. When Dima talks about delivery as code, he's really talking about a whole new way of working, where we get to what's called spec-driven development. That means your process has to change. I have been in IT for 25 years. I know I don't look that old. When I first started out, it was around moving from waterfall to agile. Companies are still struggling with that today. Now we're saying, "Hey, we're going to introduce this new way of working." We have to get over the fear and resistance from people. Once you get to some level of accomplishment, there's yet further improvement. This is a long journey that people are on to get all the way there. We do luckily have some really great case studies like PostNL, where we are delivering agents, we are getting them to this new world, this new reality, and that is, as Dima said, that moat is the fact that we have so many of these projects right now, and we're learning from ourselves and getting this experience that we can then bring to our clients, and that really sets us apart. As FB mentioned, we've created something called AI/RUN, and that's our suite of consulting services and education and tools around how to drive this transformation for our clients. We're focused here on engineering. Nir and Eli, who are going to speak next, they're going to talk about how we're doing this for the business 'cause there's a lot of similarities here. I'm gonna double-click into each one of these for a second. The first one is blueprints. Dima, you talk to a lot of CIOs. How many IT leaders can really articulate the current levels of productivity for their organization? Well, not very many. Definitely not on the second meeting. If the board is saying, "Hey, I wanna see 20% productivity boost from AI," that's a problem because they don't know what their productivity is today. For the last many years, I've been at EPAM for eight years now, we have something called Engineering Excellence. It's what makes EPAM so special, our engineering talent, how we really raise the bar in our delivery centers, in our projects, and we have a consulting offering that we've been running with our clients where we help them baseline their teams, their performance. We establish those KPIs and then build improvement plans so that they can be more agile and leverage DevOps and get to continuous delivery. We're able to take that same methodology, go to an organization, understand how are they working, and then from that figure out, okay, where is the place that AI is gonna have the best value for you? Instead of just saying, "Hey, let me, you know, be haphazard," we can be really targeted in which agents we build, the education, and then we can track the progress. We win projects because we can really articulate, "This is how fast you're moving today. This is your current levels of quality, and then here's the benefit of of AI." We have a really great case study with Edward Jones. We're working with them right now. It started a year ago with a pilot. We were able to show with our products and copilot the efficiency gains we could deliver in a short amount of time, and now we're in the process of scaling it out to the rest of the organization, and we have many of these projects happening right now. Dima showed you this picture, delivery as code, and I just wanted to go back to it for a little bit just to articulate a couple things. In the blue boxes, which maybe are a little tough to see, these represent different agents, or maybe it's agents calling agents. There's maybe 10 or so, maybe a little bit more, in this picture. If you're an organization, you can't just apply agents blindly to all of your teams. Every team supports a different application. A large enterprise could have thousands of applications that make up their platforms. What that means is that every team is going to need a different set of agents tuned for them. They have different tools, different technology stacks, different ways of working. The scale of this gets pretty big pretty quickly. What we have done is we have built a set of tools for ourselves under the AI/RUN platform umbrella. We have things like DIAL, CodeMie, ELITEA, Agentic QA, which we can bring to a client to accelerate their adoption. As well as we can handle how you can take an agent and basically copy and paste it and tune it quickly for the next set of teams and manage that at scale with the observability and governance that's required for a large enterprise. Shameless plug, we have a booth, so later on if you wanna see a demo of the tools, we can definitely show you. The tools are real, and they're spectacular. We built these tools a couple years ago. It was really important for us to be able to use them to learn and now, we definitely have projects where we don't use our tools, but what it allows us also to do is quickly understand what are those people and process limitations that are preventing wide scale adoption at a client quickly. We can bake this into our own projects. If a client's going through the transformation that takes, you know, many months, maybe years, we can come in with our tools quickly deployed with our full stack agentic engineers and really be able to deliver the value of AI quickly. Then lastly, before I hand it back over to Dima, when you talk about level one, an agile team, people are working in silos. When they start to use AI, they can create some efficiencies for their tasks. In the industry, we've had this term called a T-shaped engineer, and a T-shaped engineer means that I have this one skill, maybe I'm a mobile developer, but then I can also maybe do some API development and maybe some backend work, right? That's T-shaped. With AI and agents, I can really deliver on this promise because that T-shaped person can be sometimes a unicorn. With AI, I can give people agents to really help expand what they're able to do. I could have a front-end developer who now is able to do, like Dima said, full-stack engineering. They can do work across all levels of the application, of the platform, and do many different things. Now with AI, they really can run the entire software factory, that delivery as code. Now what we see in our new teams is this combination of this full-stack agentic engineer with combination of product and design, and this is how we deliver products in this AI-native world. Dima, I think you're gonna talk to us about why, while this might shrink some of our teams, the demand is actually far bigger. Yeah. Thanks, Adam. Now I'm also eager to look at the tools again. Adam just took you under the hood. Now let's talk about the implications to the market. The common assumption is the faster we can go, the fewer engineers you need. For a lot of work that's true. We definitely see this on the ground. At the same time, this is actually not the case in many places where we operate with our clients. There is a fixed pile of work at the top. Maintenance, application support, second-tier applications development. There is only so much work that you can do, and this pile of work is doomed to be shrinking over and over. All the firms that operate in there, they're all exposed. As I said previously, this has not been the place where EPAM was generally operating. Where we operate largely is below the waterline, and this is where we see infinite backlog space. Our clients have been sitting on years' worth of queued work that previously they were not able to attempt. Product modernization, technical debt elimination, new product development, just higher velocity and productivity deliver more and more features for their own clients. A lot of this work was put on hold or was tabled for the reason it was too complex, too expensive, took a lot of time to deliver, or simply was not possible because of technology limitations. Now AI makes it possible. Edward Jones, they had a dormant mainframe authorization program that was in a slow-motion mode. Now with our AI/RUN platform and the plans, we out-competed incumbents, and now we are helping them to deliver, and now it is active. Baker Hughes, we are a strategic engineering partner for them and helping them to work on a variety of different strategic programs in the range from data products to field-level AI assistance across all of the operations. Nelnet, we came in, and we helped them to accelerate their velocity. We helped them to define the new ways of working. As we increased our velocity, they wanted to do more of that. They increased their expectations, how many new features they wanted to deliver, and we scaled our footprint. More speed, more demand. Firms built on fixed-demand where are competing to deliver the same shrinking amount of work for cheaper. Efficiency without growth is a race to the bottom, and EPAM has not been operating there. We live below the waterline. Every time we get faster, clients are attempting to do more, and that's today's picture of demand. Now let's talk about what's coming next. Everything that we are building today, the agentic ecosystems, the agents orchestration, the enterprise hardening, that's the infrastructure that autonomous agents will require in future. Clients are paying for agentic delivery today and tomorrow it becomes the autonomous layer. Moreover, these autonomous agents, in the first place, will be attacking this top of the iceberg that I showed on the previous slide. Lower complexity, lower stakes work where we have not been operating, and this is where we can actually enter there as agents and agentic platform builders, exactly the type of complex engineering work that we've been famous for, and we can enter there as builders, not as incumbents that are protecting the margins. Let me repeat the four key takeaways and the four points that we started from. Enterprise complexity is growing. Every layer adds another, and demand for complex engineering is infinite. Second, AI creates the new engineering discipline that is difficult to master, and engineering depth is our moat. Third, we are agents builders. We are agentic platforms builders. We are codifying delivery in new ways to accommodate agents-first mentality, and we are scaling a new type of engineering profile to run it. Fourth, the investment that we are making and the work that we're actually delivering today for our clients for agents, that's the foundation for autonomous enterprise that is coming tomorrow, and with every engagement, we are getting closer to it. I started with the question, if coding is largely solved, why do clients need EPAM? Coding was never a hard part. Software engineering was. The better AI gets at writing code, the more what we do matters. Now I want to show you the video, the client testimonial from Larry Fitzpatrick from OneMain Financial. Thank you. Hi, I'm Larry Fitzpatrick, CTO at OneMain Financial. OneMain is the leader in offering non-prime consumers responsible access to credit. We offer hardworking Americans personalized lending solutions, including personal loans, auto loans, and credit cards. We operate across 48 states, online, and in 1,300 branch locations. I lead our technology strategy and the teams building the digital data and core platforms behind our growth. I joined six years ago after AWS, and I've spent my career scaling technology organizations at the intersection of innovation and execution. In 2023, we made a deliberate decision that generative AI would change our industry, and we would adopt it responsibly. We started with optimizing our guardrails for the unique risks of gen AI so teams could move with confidence. One of several strategic opportunities we are focused on is our product development and operations life cycle. Despite rolling out tools to teams, adoption was uneven. We met with many potential partners. Most sold slides and could not demonstrate performance. EPAM showed us how they were already working this way inside their own teams for over two years. We chose a partner who had done it, not just described it. Late last year, we engaged EPAM to work with the organization. It spans about 100 teams across the full product development and operations life cycle from product strategy and design through build, release, and run. EPAM didn't bring us a point solution. They brought an end-to-end system, a clear methodology, a working platform, and experienced practitioners who operate as one team. We started with structure. Their SDLC maturity model gave us a simple progression, AI enabled to AI engaged to AI native. On the platform side, we defined an AI agentic ecosystem tailored to our environment. EPAM deployed their AI/RUN Agentic platform, and we integrated it into our stack. SSO, Jira, Confluence, Git. The tools meet our teams where they already work. We are still mid-journey, but engagement across our teams has exceeded expectations. The energy is real, and it is translating into meaningful results. This is a journey, not a destination, and we've accelerated greatly partnering with EPAM. Good morning, everyone, and thank you once again for joining our Investor Day. My name is Nir Kaldero. I'm EPAM Chief Data and AI Strategist, and I'm on stage with great friend of mine, Eli. Eli Feldman, CTO. Together we lead our enterprise AI transformation agenda on the business side. Today, we want to show you how we help our clients accelerate their journey towards an AI native enterprise through robust offering portfolio, differentiated delivery playbook, and end-to-end capabilities. Our goal is simple. We want to demonstrate not just what AI can really do, but why EPAM is uniquely positioned to win in this era of AI native business transformation. We will walk you through four core areas around AI business transformation. The first one, how AI native transformation is reshaping business innovation and operations, and how EPAM accelerate the journey with meaningful impact and growing book of business. Second, how our unique AI/RUN transform playbook turns strategy into measurable business outcome. Third, how strategically we expand our service mix to support and lead the next wave of AI adoption to successfully support our clients. Lastly, how are our clients' biggest AI challenges driving long-term structural growth tailwind for EPAM for both business and engineering altogether? Let's dive in. Thank you, Nir. We see this space transforming approximately along the same ways that Dima and Adam just described. There is maturity levels, there are stages, which organizations go through. The most foundational stage is start optimizing current operations. Easy place to start, but that requires a very meaningful foundation. Adam and Dima were talking about the foundation in engineering. That is a critical ingredient. Must be there. This is not your grandfather's business intelligence capabilities. These are foundational platforms and capabilities that need to be put in place all the way from engineering to data platforms to business capabilities to enable that. Once we solve that aspect of the challenge with our clients, then we can actually start transitioning to building business functions. Now, to make it very clear, this is not about just bottom up. The bottom up is sort of the foundational and technology enablement. It is critically important, but that's not the only pathway. The other one is the top-down, understanding the business case, understanding what we're actually optimizing in the business. We'll go through some of the examples. Once we figure out that initial optimization space, well, we can now focus on growing the capabilities, running maybe even semi-autonomously the capabilities that these organizations have end to end. Once we capture all of this intelligence from the business process and the capabilities and the data assets and governance that is put in place to run that capability, then we can start identifying these new business opportunities for our clients, working with them together to bring that to the market. I'll give you two examples of work that we have done with our partners, with our clients. Critically important, each one of those started pretty much in the same place, the foundation. Cannot skip that. Have to enable foundation. Have to have the right engineering in place, have the right data platforms in place, the governance, the observability, all of these capabilities just to start even within a simple business process optimization. Once you have all of that data, well, all of a sudden, you can actually see how you can start optimizing, how can you build agentic AI around the business process and start optimizing. In the first case with a global cosmetic manufacturer, that first business case was demand prediction. We wanted to predict what actually sells in stores. We did that. The only challenge is simple if you know the demand, but you don't have the supply, you didn't really solve the problem. The business is not really benefiting. Well, the obvious projection from there was let's try to figure the supply. The compounding problem, because you need to figure out the supply from the manufacturing process or maybe even before that all the way to when the product hits the store, is actually a compound data problem that is much more significant than any one of the individual elements. Just to give you a sense from a supply chain economic impact perspective within this organization, a weekly 100% risk reduction in this company from an economic impact perspective. Sales versus costs is about $16 million a week. In the past, before any of this was implemented, humans looking through dashboards again that old fathers, grandfathers sort of BI system, dashboards and reports and stuff like that could solve 30%. It's meaningful. $5 million in economic impact they could have solved it. There's the long tail. When we started introducing the capability and sort of integrating all of the data together and working with the supply chain organization to figure out their value stream business process and all of that, we realized that about 50% of what AI actually recommends within the 30% slice still is very much consistent with what the organization actually was doing so far. Excellent result. It actually recommended the rest and almost closed the entire risk gap of the $16 million a year. A week. Sorry. This opened another interesting conversation. As Dima and Adam were saying, Dima was saying about sort of SaaS platforms and package capabilities and stuff like that. You see, vast majority of organizations out there, manufacturing organizations, supply chain organizations, CPG, and all of that, they have to rely on packaged supply chain tools because building a custom supply chain implementation across the board is extremely expensive. In the past, there was no ROI for that whatsoever. The largest supply chain organizations maybe, but most organizations could not. Now, the moment we solve the supply chain from manufacturing to store, all of a sudden they say, "Well, we have another tail of that problem. How about from the manufacturing end to the warehouse to the ingredients?" They had another packaged that was solving that, but the two were not really connected. They would manufacture one thing. Demand is something completely different. They optimize for that risk, sort of there is massive problem in between. Now, the implementation of that end-to-end supply chain, custom-built for that organization all of a sudden is a viable alternative to several complex integrations off-the-shelf tools, SaaS, platforms, et cetera. All of a sudden, we're actually capable of solving a significantly more meaningful business problem for the organization while leveraging everything that we have been talking about so far in terms of technology enablement and data enablement and governance, et cetera. Another observation that you sort of see on the slide, this field is continuously expanding. You prove one case, not prototype. Prove one case in production. Organization actually seeing economic impact. All of a sudden, well, we have this other business case. Another business case. And then it's expanding pretty much exponentially in that case, even within an individual organization. AI enables that because all of a sudden implementation is cheaper, so you can actually leverage the same budget to do significantly more work. I would like to speak about another client. You would think that CPG, well, not regulated space, pretty easy. But the reality is risk-reward in regulated organizations. The next case is a major global pharma. In global pharma, the foundation was exactly the same as before. Build a foundation, build the data capabilities, build the engineering capabilities, solve a business use case. Once we have done that, this client actually designate as a strategic partner for the entire stream of work around AI. They said, "Okay, we have another major business problem. Clinical trials." Clinical trials, 1% of defects in clinical trials. Just 1% of defects in that process cost the organization $28 million in economic impact because it delays drugs to market, like all of that stuff. Most of it is a top-line impact. It's not even optimization. It's not really even cost optimization. Now you, if you are able to solve even into the low double digits, in that case, you actually have a very meaningful top-line impact on that organization. Once this organization learn what actually existing setup means, then they are capable of understanding their assets. Now we know what our clients need. We can actually convert that into something that is significantly more meaningful. You have two examples here. One is a multinational for consumer lawn and garden products. They actually leveraging all of the foundation and all of the capabilities that we have built in business optimization, said, "Well, we can go DTC, direct to consumer." Like, we couldn't do that before. We were selling through resellers, like, all of our life, now we can go direct to consumer. A clear business value that was enabled by AI as well as all of the other work that was done. Swiss Re, which you will actually hear much more details in the panel later on. They realized being a reinsurer, they realized that they actually sell data. Again, all of that foundation actually paid off and enabled a new line of business for them. The reality is that EPAM wins at the first stage. We help optimize because we deeply understand the technology, that sort of bottom-up enablement capabilities, the technology, the engineering, and the foundation that we can build to our clients with AI-native enablement of course. We win in growing and running the business for our clients because we can layer the rest of the pie from a business transformation perspective. We understand the people transformation, we understand the business, we understand the value streams, we understand the flows. Now we can actually layer the two together and significantly enable these organizations as well. We can leverage all of the deep agentic capabilities, all of our experience over the past 30 years building go-to-market capabilities for our clients, and actually enable them to create new set of businesses that they have that are AI-native. Nir, please give us the details on. Thank you. Oh, sorry. One more slide. One more slide. Sorry. All of that is actually quite systemic. Adam showed the slide before and we work very closely with the technology organization obviously to enable these capabilities, where we have the blueprints for the technology enablement, the prompts, the sequences, the workflows from engineering perspective. We actually develop the same from a domain and industry expertise, so we come to the customer with, like, deep understanding of the value stream of what they actually need to solve from a business perspective, enabled by technology out of the box and we're capable of solving that. We understand that none of this is possible with individual contributors. We must build networks of experts to be able to solve these complex problems, and these are networks of experts that include, again, engineering is critically important, but people that understand people, change management, transformation, domain, industry, governance, and all of the other stuff that needs to be in place to make it work. Then the tools and the platforms that need to be in place to enable that. The time to market needs to be accelerated, so we have to come with some accelerators, some harnesses, some productized offerings to be able to make it faster and more effective for our clients. Now, Nir, please. Take us through some of the details. Thank you, Eli. Thank you. All right. Now let's talk how we are expanding our strategic capabilities to lead the next wave of AI adoption. Successful AI adoption comes down to three kind of like main pillar. Think about it as a three-legged stool. The first one is the data, which is the fuel and really the foundation for AI. The second one is technology, which is the environment and the infrastructure to really deploy AI and use it to scale. The third one is people, culture, and process, which is probably the most important pillar here, where you really want to make sure that what you built is adopted and then delivering the business value following the investment. Across these three, we are expanding our AI strategic service capabilities to help our clients transform at scale to ensure we stay ahead of the market and help them. Let me walk you through these kind of like four areas of expansion. The first one, we are reshaping our consulting model into something entirely new. AI-native, verticalized consulting built with and for AI. This isn't just traditional advisory. We use AI to conduct consulting itself. Instead of slide decks, we deliver prompts. Instead of static artifacts, we enable small language models across evolving processes. Instead of isolated recommendations, we co-design simulations with agentic tools, and we really aspire to help business leader run scenario planning with AI agents in days and not weeks or months even. We deliver consulting also for AI, the practical building blocks that make AI successful in productions all the way from operating models, governance, responsible AI, cybersecurity, adoption programs, and value tracking. Our consulting proposition is built for one purpose, moving AI from experimentation to production at scale. The second one is we are building the future of business operations, as FB mentioned. We are experimenting with and plan to disrupt the market through an agentic-led business operations offering, where we design, build, and run high-end processes powered by agentic AI. This lets us expand our share of wallet, evolve our service mix, and grow our total addressable market through next gen managed services. The third one is where technology and domain expertise truly converge. We are building deep industry knowledge with strong AI capabilities and acumen all together. Through our proximity to clients, we are developing industry-specific data models, co-creating vertical ontologies with strategic partners, and assembling pre-built agentic workflows tailored to how industries run. The payoff for our client is simple. Faster AI deployment in their specific context with less risk and greater precision towards the ROI. The fourth one, we are evolving our accelerators. We have been already expanding migVisor into an agentic-led migration platform. We also extending for quite long time DIAL as an agentic orchestration platform. Think about it building agents with prompts. You have the ability to deploy mixed frontier models and ensure that AI is really deployed at scale all the way with governance, security, and FinOps from the get-go and from the start. Together, these kind of like four capabilities position us to be ready and ahead of the market to deliver real measurable value for our clients. Let me close with why we believe AI is a long-term structural tailwind for EPAM. Real AI business transformation isn't really just about deploying models or tools. It demands business model reinvention. Think about it as the culture and the mindset shift that enables completely new ways of working. Process reimagination, targeting the right workflows and designing AI enhanced experience. Data monetization and modernization, really breaking the silos, capturing new data, and building the architecture and the semantic layer for reusable real-time intelligence across the enterprise. Obviously other critical services and elements across the end-to-end AI innovation life cycle all the way from AI strategy to MLOps and AIOps. Think about it, this complex business transformation work stream also generating significant downstream investment in core technology and engineering demand to enable the foundation to run, deploy, and use AI at scale, which altogether, if you think, creating a significant opportunity for EPAM to lead in the market. The business transformation work and the technology work also deeply interconnected, and we see both of them are growing. We are uniquely positioned to deliver strategy and implementation simultaneously to enable the full deployment and full scale reinforced by our AI native talent and unique playbook. Our end-to-end capabilities is really and truly our competitive advantage. This is why we believe EPAM will continue to capture market share as AI accelerate globally. With that, let me conclude and have some kind of like key takeaway to leave you with. The first one is we are driving our clients' AI native business transformation at scale. Few great examples that Eli show on stage. We are leveraging our unique and proven AI run transform playbook on the business side to turn AI strategy into measurable business outcome. We're expanding our service mix to unlock new opportunities while staying ahead of the market, to support our clients' AI adoption journeys. Our clients' biggest AI challenges create long-term structural growth tailwind for EPAM within both engineering and consulting strategy simultaneously. With that, it's my pleasure to introduce our next client testimonial from Guy-Laurent Arpino, Chief Information Officer of LDC. Thank you. Thank you. My name is Ahmet Tezel, and I'm the Chief Innovation Officer at LivaNova. My role is to lead end-to-end innovation in the company. It was clear to me that we needed an external partner to help us out in creating a cloud platform and products that go with it, and I had experience with EPAM from a previous company, and it was a good experience. One of the challenges if you're an epilepsy patient is that you have to go to a physician's office about eight to 10 times in your first year post-implant. The reason is that you go there to get your device adjusted with respect to its parameters. Now, this is not easy for epilepsy patients because they're pediatric patients or if they're adult patients, they usually don't have a driver's license. It's a complicated task. On average, you travel more than 30 miles for each adjustment. Doing this in-house in a hospital setting is difficult. Now, there is a huge unmet need here where you can do this adjustment in a remote setting, where the physician can connect to the device remotely and talk to the patient and do the necessary adjustments. That's the program that we developed with EPAM, where EPAM was able to create for us and work with us a secure private cloud connected care system that enables physicians to connect to our products remotely and adjust the parameters of the patient's device remotely. I envision that we will continue to work with EPAM. We now have the first FDA approval for our first franchise, our epilepsy franchise, through the product that we developed together. I envision that we will continue to work together as we expand the partnership into other business units that we have in the company. We have a broad neuromodulation franchise with different disease states that could benefit from cloud-connected care, and we also have a cardiopulmonary franchise that can certainly benefit from having a connected ecosystem for their devices. I envision that we will continue to work together with EPAM as we roll out our digital ambitions to our broad business units. That was clearly not Guy-Laurent. You know, it couldn't be an EPAM presentation if it wouldn't have some mistakes. The clicker works, so that's typically our problem, but now we switched off a video. You're going to see Guy-Laurent in a later stage probably instead of live and over, we're going to play that video. Excellent. We're now gonna turn to our question and answer session. I'm joined by FB and Elaina here for about the next 20 minutes, call it. Just a quick couple of points for those in the room. Just please raise your hand, wait for the mic to come to you, state your name and firm, and we will get to as many questions as we can. We also, of course, covered the overall strategic overview, our transformation, and then our AI native pieces of the business. We kindly ask to keep your questions tailored to those sections as we have much more coming up later in the afternoon, including our financial imperatives and multiyear outlook. With that, we'll go ahead and open it up. We'll take one here in the front. Mr. Bergin. All right, thank you. Bryan Bergin from TD Cowen. Appreciate all the color you've given so far. I wanted to ask on the go-to-market transformation. Trying to understand really how material this change is for you. You've talked about a, like, a consulting-led approach in the past. What are you gonna be doing differently now? I think you also mentioned maybe potentially some client-facing personnel changing. Just talk about how you're gonna manage execution risk around that. Let me go back a little bit. Bryan, good to see you, and thank you, thank you for that question. Let me go back a little bit about EPAM. EPAM was historically operating in a seller's market, right? If we created the capabilities because of the resource shortages, people were coming to us and it was very much us showcasing our capabilities. I think in the last years, we learned that it's much more of a buyer's market, which means that we need to be more proactively marketing our services to them and actually start creating a more targeted go-to-market motion backed by marketing. At the same time, the way how we managing our client relationships are also changing, and we started to make those changes probably in the last one or two years. Very much focusing and becoming more client-centric and very much highlighting the way how we're solutioning with our clients. Also, clients right now increasingly more transforming how they're delivering their businesses, as Eli and Nir was talking about, and we need to provide help to them. Elaina, could you add something to this? Yeah. Thanks, Bryan. Good to see you. For sure there's a couple of things going on. As FB said, we have to go get more of the business than we've ever had to before. We're actually changing that go get motion not just to sell AI, but changing it with AI. There's a fair amount of training that's already happened. There's more in terms of sales enablement and sales training to come. Yes, I think that there will be some rotations in the field. I think that's natural and expected and, in fact, welcomed. One of the biggest changes that we've made this past year is really integrating the industry consulting groups, which were historically for us more of a standalone service line into our IBUs, into our industry business units. What that's creating is sort of these high-velocity teams that I spoke about and that you heard about now. Is it a risk? Probably. Is it absolutely critical? Definitely. One here in the front. Jason, please. Thank you. Jason Kupferberg from Wells Fargo. Really appreciate all the detail. I wanted to ask about the these full stack agentic engineers. Interesting new role sounds like. Tell us a little bit about the profile of these individuals. How many of them do you have today? How many of them you think you'll have in two or three years? Jason, good to see you. I think it's a really good question. Clearly, this is something which we are growing rapidly right now. We have very much focused on this space. You will hear probably in 1 hour or so from now from Sandra and Alexei how we actually creating, how we finding them in the organization, and what training program we are putting through that. Actually, this capability is growing really fast because that's the real focus area. What we're doing is we're identifying them. We are actually putting through them with a rapid pace of understanding it, and we probably in the last just 3 months, we just doubled the capacity of that capability or that headcount. This is something which is going to be our standard motion going forward. In every discipline, every line of business, we are basically pushing our engineering teams, but even account managers and delivery managers or the sales team at how to adopt and how to use AI. Just two weeks ago, we launched quite an aggressive and pushy program to make sure that our salespeople, account managers are actually using agentic tools to not just deliver their account plans and solutions, but actually understand fully how to deliver these applications. This is ongoing effort. That's where our investments are going, and we believe this is what's going to differentiate us and going to allow us to really scale in the years to come. Thank you. We have one here in the front. Thank you. James Faucette, Morgan Stanley. Thanks for putting this on today. I wanted to ask a little bit, as you change the engagement approach and sounds like some of the development approach, is that gonna necessitate also a change in the way that things are architected from the beginning? And how does that impact things like sales cycles and project scaling and that kind of thing? Thank you. Good to see you. Absolutely it's changing. Actually, if you will, just a shameless plug, as you are in the audience, go after the session, we have a whole video actually explaining to you how we are using what we called AI factories in the sales process, how it's actually integrated in our RFP creation, RFP responses, which is really going to change the way we are going to market and actually sells our efforts. It is changing not just how we're selling, it's not just the way we are contracting. It is changing how we are architecting the solution, how we're putting together the solution itself. We will be talking about how we quality assure all the proposals and all the estimates using AI. This is very much ingrained into our go-to-market motion, the way we delivering, the way we are go to market and actually how we build the solution and how we're using AI in every possible step where it's possible. Where it's not just possible, where we are able to figure out how to plug it in today. We're finding new and new ways, you know, every day. Two over here. Please. Hi, it's Bryan Keane at Citi. Can you talk a little bit about going after that fixed demand, some of that work that you guys didn't do traditionally that was more labor arbitrage, how you guys can get into that market through AI, and how fast can you disrupt that market by coming in at different prices? I think it's a good question. I think we had early indications that we had success in this space in the last months and weeks. We made many proposals in this area. It's probably too early to call a full success, but we see real promises in this area. We're going to, again, shameless plug, you're going to see some amazing videos and demonstrations behind you around how we're going after the manual testing space and how we're going after the intelligent operation space with AI. How we're helping that in this area. Also, we're going to start seeing capabilities, how we're actually doing BPO automations for some of our clients. Actually we have public case studies around it where our clients are starting to see real ROI, us replacing more traditional call center agents with AI-based solutions. How fast it's going to scale, it's probably early to tell, but we are seeing demand interest from our clients. Because we coming in with a very fresh point of view, we coming in with a new ways how we approaching it, with a new price point, a new way of delivering it, new way of taking advantage of AI to do knowledge transfer. This creates quite a buzz in our community. Can I? Yes, absolutely. Just to maybe put a point, a fine point on it, for us, it's a transformation pitch. It is not a labor arbitrage optimization pitch, and all of the attendant things that go with it, including organizational design, platform architecture, et cetera. It's much more than just a labor arbitrage market capture opportunity. One here in the front, then next to you. Thank you. This is Puneet from JPMorgan. As you pursue AI native SDLC, bring AI into SDLC, which changes the way you engage with your customers, talk to us about change management aspects, like from clients' perspective. Like, are they ready? Or more importantly, are their employees ready for these changes? Will, like, all the recent news flow around Anthropic and the development there in cloud and everything, has that changed their behavior in any way? I think, Puneet, great question. I think if I want to summarize it is a change management process. We're going engagement by engagement, project by project, and we're talking about thousands of engagements which we are migrating, which we are elevating in terms of maturity. Are our clients' employees ready? No. It's an opportunity for us. We are giving them education. We are giving them advice how to change organization, how to introduce new tools, how to actually go through this whole education coaching process. Most organizations just went out, as Dima and Adam talked about, went out and bought the tools, and they said, "Here you go. We expect you to be 15%-20% more efficient. You know, couple of months later, they found out that it's actually a J curve and their productivity kind of dropped. They said, "Okay, why don't I use some online resources? This is where you can read about it, and there are some forums." Nothing happened. This is the point where we are entering into the picture, where we are really start advising them and coaching them how to actually mature the engagement model. They are not ready. I think all the changes you are referencing, which is, Anthropic or, OpenAI, launch of Claude Code or Codex, this is only for the really mature clients and mature engineering teams. If you just launch in a legacy code base in a brownfield, any of these tools, these tools go, you know, go wild, and they actually not going to create any productivity because you need the specs, because you need to describe the brownfield itself, the expectations, and you need to have the right tooling in place. It takes a while to adopt. It's a change process, and we see a multiyear adoption for the enterprises. I think we had one here, and then we'll go to the one over there. Thanks very much. This is Nate Svensson from Deutsche Bank. I'm gonna kinda build on Puneet's question here. I really like the slide with the three levels of AI adoption. I thought that was a useful heuristic. Sounds like most companies are on that first inconsistent and ad hoc usage stage of AI adoption. Your differentiation and moat is going from the second to third stage. I guess the question is, if most companies are in stage one today, how do you help them get to stage two to ultimately get to where you have the most competitive differentiation? Why are they gonna choose EPAM to go from stage one to stage two versus a different system integrator, other sort of competitor, and how do you maintain that client relationship as we continue to progress? Very good question. I think why they're going to choose EPAM, because we will go in and show you not just slide decks. This is the case where we're showing slide decks to you, but in most cases we are coming with real examples, real blueprints, real proof points, how you're going to get there, very practical. How can we actually go in there? It's very hands-on experience. Our clients are seeing that the leadership team who we have, the people on the field are really understand how to make this happen. This is the experience. When they talk to me, they actually kind of see on my computer, I'm running a Claude Code, and it's a very different discussions when the CEO really starts talking to them about the best way how to use in the enterprise for all the different purposes agentic tooling itself. It brings a level of credibility. Most organizations actually not even at level one. Most organizations are still level zero. They haven't purchased the tools yet because they never done the investments. It's just in the last six months when people really started to understand that this is really happening. Previously, based on all the different data points, people were kinda skeptical. Now skepticism is gone. They start investing. They, the only thing what they are able to do is go out and make those purchases. That's why probably the revenues of these companies are skyrocketing right now. The adoption is very, very difficult. We are going out with the blueprints, with the runbooks on how to make the transformation with the educational materials, understanding how to actually go through step-by-step the change process, understanding how to mature engagement by engagement, because it's not a top-down, I would say, big bang. It is happening. You have to do it project by project, going step by step, and as you are maturing these engagements, you can go to the next level. We have examples, and we can actually show how you're able to execute that in an organization such as EPAM at 60,000 people scale, and that's very unique. That's why they're called foundational services for us. Let's go here, and then here. Thanks. It's Jamie Friedman from Susquehanna. I was revisiting my notes from Dmitry's talk about the four reasons to need EPAM: enterprise complexity, engineering moat, agent building, autonomous enterprise. If I messed those up, I apologize. My question is, if those are the reasons to need EPAM currently, I'm wondering, does it change the relevance of the global delivery footprint, and does it potentially argue for a bigger on-site, on-shore presence? That's a great question. I think what we are seeing right now is our clients and enterprises, the same time they're trying to mature AI SDLC, mature the engagement model, mature the maturity what they're doing, same time they are executing in parallel other strategies, such as moving to GCCs in India or other locations. They're coming to us, how can they upskill their existing so-called legacy GCC with new skills? How can we help them to increase their internal efficiency? Just the other week, I was talking to our client when making this pitch. They are actually expressing their need that can you engage with EPAM, with the EPAM scale globally to tackle their own internal legacy. Their own legacy is not on-site. Their own legacy is it's a global footprint with different GCCs in different countries, starting from India to Spain to, in this case, it was Portugal and Slovakia. That's where engineering is happening today, and you need to meet your clients where their engineers are. For us, we don't foresee that, and actually later on, you are going to hear on the panel how we're seeing all these things play out in each and every different geographies where we are. Surinder Thind with Jefferies. Following up an earlier question about the client journey and going from level one to two to three, and I think, FB, you mentioned that maybe a lot of them are even at level zero. Can you maybe talk about the propensity of clients to move away from level one in the sense that if the models continue to get better, right? We look at the journey over the last couple of years, would a client not want to continue to try and do more themselves, especially if the models continue to scale at the current pace? And are we in a situation where we have to wait until maybe there's a more maturing of the technology before clients move to level two and three? Or, or what gets them across that line? Because it just seems like industry demand remains relatively tepid. Thank you very much. It's a good question. Okay, so I think the models are maturing very, very rapidly. We all know that the capabilities. Also the price point of the certain level of capability maturity is continuously dropping. For different business scenarios, business cases, you need different level of maturity. Depending on your price point of engineering, depending on the business case you would like to use AI for, right? There is different entry points. It might be possible that due to tokenomics, the today for one company this is affordable and or actually economical to deploy AI today, or some decides to wait a little bit later while the, let's say, the models mature or the cost drops because there's two things happening at the same time. Newer models going to enter at the same level of price points where they are today. Old models continue to become cheaper as the token price, execution price, inference costs for all those models are dropping. Some people are starting to deploy and actually actioning on this as they reach a certain entry point, and some people are waiting for newer models, as you're saying. Maturing, going through a maturity model, it's not really optional. In order to get access to the capabilities of the model, you have to go through this maturity. One way or the other, if you wanna tap into the power of the models, you will have to go from one to three. You're not going to get the benefits at level one. Actually, probably you're going to, as the models continue to evolve, you will be continuously even more disadvantaged by staying on level one. I don't know if it makes sense, but that's probably the right answer to this. We have time for one more question here in the front, please. Jonathan. Jonathan Lee from Guggenheim. Thanks for hosting. FB, you mentioned, you know, different price points as it relates to models, but can you expand on EPAM's pricing strategy overall as it relates to how your new go-to-market and your AI-native approach impacts your pricing strategy going forward, especially as you balance, you know, agents versus perhaps higher cost team structures given talent scarcity? Jonathan, thank you much. It's a great question. I think as you saw from our results, we continues to be predominantly in a time and material model and we actually also communicated too that we were in Q4 we were successful getting rate increases from our clients, which actually indicates to us that the clients are receiving benefits of the more value which we deliver to them in the T&M model. But also I have to tell you that most of the times the tokens are paid by our clients because we are operating in the client's infrastructure due to security reason, due to data confidentiality. In that infrastructure, the clients are the ones who are deploying the models, and they're paying for the tokens. Going forward basis, as we are migrating away or transitioning away from time and materials to more advanced, capabilities or more advanced contracting models, we will be seeing that it's going to be part of our, commercial model. We're going to factor in the price of the tokens into our, model itself on top of it or on, or in a more maybe on a transparent way. It's a work in progress how we're going to charge our clients the model, the tokens because as the tokens is the price is very volatile, so it's very difficult to figure out how to price it in at this point of time. We expect that once we are more in the fixed price or more advanced models, the cost of compute will be included in our price. Last but not least, I think one takeaway that our AI native projects and revenues are operating at higher profit levels compared to EPAM average. They're more profitable. That wraps the first Q&A session of the day. We're gonna take a break and reconvene here at the bottom of the hour, so 10:30 A.M. for those that are attending virtually. For those in the room, please enjoy some refreshments and drinks, and then we'll get back to our seats here. When we come up next, Arkadiy Dobkin, our Executive Chairman, will kick us off getting into our engineering DNA. Thank you very much. People are probably familiar with the MIT report that boldly states 95% of companies are getting zero return on their AI investments. You don't have 10 years. You have 2. Three, maybe. I think AI will be transformational for the clinical experience in surgery. I think, it's going to improve patient outcomes. It's gonna reduce, burnout and burden on surgeons and nurses and respective teams in the hospitals. At least 90% of the AI projects that are rolling out are failing within companies, and that's because it's an organization and a people adoption problem with AI. That we appear to be the anomalies, I think is really cool. We have a client base that is beating the trends. They're at the forefront of it. Taking something as nebulous as, and as confusing and sometimes scary as artificial intelligence and all the hype around it and turning that into, examples of really meaningful programs that EPAM is either in the middle of or fully executed, is the vision. We really are starting to unlock useful, tangible results for our clients. These all go far, far beyond POC. These are scalable deployments of AI that are really delivering tangible business value for our clients today. We ingrain it in all of our projects. It's basically nature and, fundamental to what we do, trying to improve things and make things better. EPAM is a fantastic partner for us actually on the sustainability journey and also building our global innovation strategy. We've leveraged the EPAM partnership with their expertise. Putting our best foot forward has been a huge benefit. EPAM have been a great delivery partner for us, both in terms of challenging us to making sure that we push the boundaries and making sure we're getting the basics right as well. What I think people get wrong about AI is that it is there to automate tasks and remove humans. It's gonna be much more of an exoskeleton, so it's gonna enhance people's capability, it's gonna make them faster, it's gonna make them smarter, it's gonna improve decision-making. Artificial intelligence in many ways is a complement to human intelligence and something that we should be looking for to actually propel enterprises and to propel sort of the enterprise of humanity forward. Eu já sei que nada será como antes amanhã. Mas eu sei também que você não tá falando a verdade, meu bem. Por favor, me deixa e mais, me dá um favor e sai da minha vida, porque eu sei que vou sofrer a cada despedida. Me dá um favor. Please make your way back to your seats. The program is about to begin. Hello, everybody. Good to see many familiar faces here. I'm Arkadiy Dobkin, executive chairman and founder of the company. I've been here for a long time, and passed the CEO position to Balazs in September of last year, as you know. I think being here for a very long time and hearing the previous conversations and Q&A sessions where we actually try to answer very, very difficult questions and present the picture which conflicts not in very simple terms. We kind of engineer our presentations well, and I probably, based on the years, have a little bit more holistic and casual conversation today. There are three key messages which I think important. I would like to concentrate on this, that engineering excellence is still very. Sorry. Why Kevin was. Engineering excellence is critical differentiator, and in the AI age, it's even more important to cut through entire implementation cycle. I think history matters, and similar like in previous waves, I don't think it's going to be revolution. It's going to be evolution for multiple reasons, and I think history is important to remember. I think similar like in the past, the human talent will be the critical differentiator. Everything else will become eventually equalized and become more commodity. Actually the people who deliver in the last mile will be critical. With this, I would like to, for a couple of minutes, go back to the history and explain, at least for some new people in the audience, that from the very beginning, EPAM was slightly different than other major players on IT services market. Our first clients were software companies, and for the first 10 years, 100% of our services were focusing on building products for software companies. Very, very different business. The second 10 years, we started to work with digital natives, Google's, Expedia's, Epic Games', games of the world, and actually helping them to scale. At the same time, you understand that this 20 years of our first years of existence actually established very different DNA, very different processes, very different talent selection than majority of the industry. It's important, and it's become important after our IPO when we grew very, very fast, when we were able to address the demand of completely different skills. I am using the same slide, which is already in Balazs presentation because the question which you asking and we asking ourself, is it still important? Is this engineering DNA still going to be differentiator with all this noise and rumors and credible people talking around us how code is over and maybe code is over, but what about engineering? Maybe engineering is over and what the next model will bring and all of this. With this, I would like to add opinion of one more expert, and I'm not going to read the slide, but please read it. Or even in short, the author said this: "Programmer is about to share the fate of the Dodo bird. By the end of this decade, I foresee massive unemployment among the ranks of programmer, system analyst, and software engineers." It was published in this book in 1992. It wasn't published by somebody. It was published by Edward Yourdon, who was a father of structuring programmer and critical person in creating object-oriented programming. He was a visionary and one of the top 10 computer scientists of his generation. Why I'm saying visionary? Because this book was published in 1992. His thesis was that offshoring and new programming methodologies will kill American programmers. Think about 1992. The whole offshoring in the market was $100 million from about $100 billion-$200 billion global IT. He was brilliant. Three years later, four years later, he published another book called Rise and Resurrection of the American Programmer because he admitted that he hugely underestimated entrepreneurial drive, Silicon Valley innovation, growth of economy thanks to internet, and one more point, complexity of the enterprise. He hugely underestimated that, and he was wrong in his first book. This bring us to actually the EPAM life cycle, the history, the ways from foundation to going through the crises. We started in 1993, actually, at some level inspired by his book about offshoring. We ran to the internet era. You know what? At this point, the skills which have to deliver this new type of applications didn't exist. You cannot go to the market and buy. Each of this internet, including actually created the hype, the programmers, C++, C or C++ like real people don't need anymore. HTML coders will do it. Then it was disappearing because each time complexity was underestimated. We came to era of cloud, mobile, and data, and same stuff. We as an engineering firm, we're starting to build our own platforms. It's been mentioned TelescopeAI, we will talk a little bit more about it. We also engineer not only digital platform, we engineer our educational learning platform as well, because we cannot find these people, we have to find the right candidates and develop them. That's what we did during this second era better than anybody else. That's why we were growing. This is where was impossible to predict what type of new applications going to happen. Think about it. We're talking about AI impact on existing type of applications, and that's what underestimating coming from, because the main change going to be in the future, and we don't know yet what it is. Now we're in AI era, and that's what we were covering before me, and the pattern again across all of this was that every productivity, whether from 4GL to object-oriented to open source low-code, promised to reduce builders' demand, and in practice, each time the lower cost went, the more market expanded. More opportunity, more cheaper were done new, and this new were growing like a snowball. That's why if you think about in addition to everything else, what's happening with regular productivity, which we kind of focused in the first part, entrepreneurial drive of people, innovation levels of something which you have no idea about it today, potential economy growth with AI and making everything cheaper in intelligence and enterprise complexity, which I don't think I need to explain. Even with the comment before that some of companies even didn't buy the tools. The silos of knowledge so huge in corporations, you, working there, you know. AI not going to bring any benefit unless it's all uncovered together. With this, in the AI era, it's going to be actually growing demand. I'm pretty sure about it. Not theoretically for very real. We enter the market when traditional software could never afford to serve before. The last mile become very critical build differentiation. Everything else will be equalized. We're going to address levels of complexity we have no idea about it today. Similar like think each time 10 years back. Think from AWS to Amazon bookstore. Can we imagine all of this happening? I think the shift of the bottleneck going to be up and up, and the last 80%-20%, which usually taking 80% of the big engagement because of complexity, they will move even to higher average. The 80% was relatively easy. Yes, it would be much more easier to do. I think at this situation, the people who delivering this last mile, leading this last mile, which would be very, very scalable, it's a key differentiation, and these people who has to work in ambiguity, in unknown, think very quickly because AI making everything older very, very fast. I think bringing another current authority, Boris Cherny, he's like probably you saw his podcast. He was talking about exactly importance of engineers, and this is what Dima was talking about it, this full stack agentic engineer who can coordinate. People who can orchestrate. If you think that it's very new thing, that it's a mistake. I think that's exactly EPAM was benefiting from this type of people in complexity during the previous decade. This is how we differentiate ourselves in the past. The point was that with talent we built, sometimes these type of people were not even in enough demand. We were putting them on some coding positions. We understand with our insight to the systems and to our educational learning process, which we're going to talk about in a minute, how to identify them, how to develop them, and how to scale them historically for the last decades. Key takeaways. We're probably really underestimating the scale of AI-driven market expansion and the complexity of enterprise. The second, engineering matters, and Anthropic people saying this as well. Coding simple, engineering becoming much more sophisticated. Think about it like new terms which come in like almost each couple months. Prompt engineering, okay, this is legacy. Context engineering, intent engineering, I don't know what will be tomorrow. Right talent, and this was 30 years of our focus. By the way, Dima, who was presenting here, he was graduating from computer science, but he went through our educational six-month boot camp before he started to work at EPAM. That was happening 20 years ago, and this is what's happening today. Thank you, and I would like to invite Sandra, our Chief Learning Scientist, and Alexei, who is the Head of Engineering Excellence, actually to bring much more details on what I was sharing with you. All right. Good morning. My name is Alexei Didyk. I'm Head of Engineering Excellence AI. I'm Sandra Loughlin. I am EPAM's Chief Learning Scientist. Arkadiy just showed us that we need the right talent. Dmitry and Adam gave us a glance of a full stack agentic engineer, and it was even a question from the audience, who are those people? Let's take a look. A full stack agentic engineer is not just a new role which build from scratch for AI era. It's a evolution. It's built on a foundation of narrow specialists available in the industry. In EPAM, narrow specialists, they're also already better because of our engineering DNA, culture, and excellence. Now we need to extend this foundation with a full stack development, ownership of application layers across all technologies. We need to deepen it with a understanding of AI tooling and also understanding of AI-native workflows, capability to orchestrate agent fleets across all stages of development. How we can even approach this new talent profile? How we can build it? We are doing it by breaking it into skills. Skills which are becoming less prominent and important, skills which still need to stay because I still might have, and the skills which are emerging and rising because they're becoming a new must-have. How we build those talents. To build those talents, we have our educational program with universal coverage, and we build this program using our own proprietary courses. We do not want just to use materials from the market because we believe that external knowledge need to be processed and passed through the lenses of EPAM experience, our experience to deliver AI-native work. We combine it with a formal education and informal education, running a global AI conference last year, thousands of people, 45 countries, because it's important to build horizontal connection with people, between people, so they can exchange knowledge, learn from someone next door. We run master classes together with our partners from Amazon and Microsoft. It's a very good program, but is it enough? If that seemed common to you, it is. Percent of employees who've gone through courses, who's clicked through what, how many classes do you have? Those metrics are table stakes. Worse, they're illusions of competence. Training people is not a strategy, and it's certainly not a differentiation. Leading in the AI services market requires going far beyond those basics. Building the AI-native talent that you've been hearing about today is actually a three-pronged challenge. It starts with identifying the skills that are in demand today and, critically, the ones that will be needed tomorrow. Exactly the kind of skills that you heard about this morning from Dima and Adam and Arkadiy. Development really isn't about training. People can train and learn nothing, and most people learn from informal things like reflection and practice and getting feedback. For development, there are two key things to learn about. One is motivation. Can organizations drive their people to learn even when it's hard or not fun? The second is validating the skills. If you can't use those skills in production, it doesn't matter. The most critical metric for a professional services organization is actually deployment. Can you put the right skills and the right combinations on the right client projects to create value? This three-pronged challenge fundamentally shifts the metrics that matter for talent development. Instead of focusing on number of people trained, the companies that grow people and those that invest in them should be thinking about different metrics altogether. How quickly can you sense the right skills? How fast and how thoroughly are people upskilling and demonstrating that they're using those skills in practice? Critically, how quickly are you staffing the right people to the right client projects? In this era, the future will be made by those people who focus on those metrics. You're not gonna be surprised to hear that is who we are. For years, you have heard about TelescopeAI, EPAM's proprietary 30-year, homegrown, in-the-making system that is focused on people and the backbone of our business. Today, you're learning why we keep talking about it, and that's because TelescopeAI was purpose-built to do exactly these three things. In a world where organizations know more about the chairs in their buildings than the skills of the people who sit in them, EPAM has built our business to know exactly what we need, who we have, and where best to put them. For a company whose business is people, that knowledge is competitive advantage. Before Alexei shows you the metrics that we track, please know that some of these numbers are operational and proprietary. That's why you're not gonna see hard numbers for everything. Most importantly, you can't interpret these numbers without a context, and the industry is just not there yet. They're not tracking the same numbers that we are. We believe that they will get there. We think it is inevitable, and we're excited about that, the day when they do. Until then, we're gonna offer you a glimpse into how we treat talent as a business asset. We have three functions, sense, develop and deploy. Sensing starts from market and industry. Industry first. Our practice leads carefully process all information coming from the industry on what is gonna happen in the next months and years. We do not just listen. We process and convert this information into skills. Skills which are retiring, retaining or rising because it drives the development of our learning programs. The same skills are used to understand demand on the market and predict demand on the market because we know how much new positions our clients need with AI-ready skills. I should say that this demand is quickly accelerating. It's not enough just to sense industry and the market. We need to sense our people to understand the why, how we can provide them to our clients. This sensing is definitely not only about how many training modules they completed. This sensing is about the way how they converted this knowledge into a real work experience and build real skill. We combine evidence from different sources, from the complexity of delivery of real work they've done, from reviews and assessments, how quickly they learn, endorsements from their peers, and it all together creates a universal standard applicable across all our global workforce, across all our countries. I should say that we are sensing that we have enough AI-ready engineers to cover all our client needs. Now we need to deploy. We don't want to deploy people just based on availability. We want to deploy people based on their verified mastery, based on our ability to provide fit-for-purpose engineers to our client. That's why our TelescopeAI and proprietary AI-driven matching model uses 25 different attributes to find the right people with the right skill for the right project of our clients. Results are evident. Roughly 80% of positions with AI skills at this moment are staffed within seven days, and the rest doesn't take much longer. It's about speed, because you can staff quickly, but is it a quality? Quality is here. Our NPS, in comparison from 2024 to 2025, grew by +4% and taking into account that our NPS is already above industry average. The fact that we have hundreds of university partners is good, but the way that we use them is actually what matters. Instead of relying on faculty to keep pace with AI or hope that they listen to us and change their courses, we learned long ago to engage directly with students like Alexei, like Dima, using our own instructors and our own proprietary coursework, the same coursework that we use with our people inside. This means that students in our pipeline are trained on our evolving definition of AI talent, and they're tuned for local client demand. Because we've invested in them and because we have built relationships, EPAM gets to snap up the best talent before anyone else. This model is not new for AI. It's how we've operated forever, and it's not something special that happens in one geography. We built this model in Eastern Europe and then scaled it to all of our major delivery centers around the world, and that's why, as you will hear from Larry and Vic, we can have a standard very high for engineering talent anywhere we go in the world. Four years ago, I stood here and said, "Young EPAMers can't be hired, they can only be built." That has not changed, but the value to our business has. In a world where AI native juniors aren't available anywhere on the market, EPAM has a global pipeline prepared for local client demand on day one. Results are evident. We have an engine and it's running. We are sensing the market in an industry which allows us to predict what's gonna happen next and how many people we need. It helps us to build the supply depths through our learning programs, combining formal and informal education, and then verifies the skills to be sure through the real delivery, through the production. We are able to deploy our people fit for purpose, right skills, right people for the right project. We can do it quickly and keeping quality. Deploy function goes back to the sense, and that's the way how the feedback loop completes. That's how the whole engine is working. We can not only today create several full stack agentic engineers, so many of them, we can do it tomorrow and the day after tomorrow just because this engine is what drives this success. The market commonly conflates EPAM's success with our historic footprint in Eastern Europe. That has never been correct. Our roots in Eastern Europe set the highest expectations, but this talent engine that we've been telling you about all morning is what has scaled those expectations to EPAMers worldwide. In other words, our ability to provide clients with the best engineering talent is and has always been due to what we're showing you today. A platform and business model specifically designed to sense, develop, and deploy cutting-edge talent. As you have heard through the years, what defines cutting edge has changed, but the success of our model has not. We have maintained world-class talent in every era and in every area of the world. From this perspective, full stack agentic engineers are not a new challenge for us. They're just the next frontier. Competitors are scrambling right now to recreate TelescopeAI and our skills-based organization, as they should. Meanwhile, we will continue to refine our engine and use it to help our clients get ahead. As you've heard all morning, AI is changing and expanding, not diminishing the need for expert engineering talent. In fact, AI has only made the need for that foundation stronger. Value follows constraints, and in a world of AI, one of the biggest constraints is human skills. To meet the moment, IT professional services organizations must sense what those skills are, motivate employees to develop them, and deploy the right combination of skills to the market. That's it. That's what it takes to lead in the IT services market. In this, EPAM has a 30-year structural built-in disadvantage. Thank you. All right. I wanna welcome to the stage Chief People Officer, Larry Solomon. Thank you. Hello, everyone. It's great to be here. I'm Larry Solomon, as you just heard, EPAM's Chief People Officer, and I've been in that role for coming up on 10 years now. Now, earlier in the session, you heard Adam Auerbach comment that he's been in and around the IT industry for 25 years. I've been in and around the IT industry for 40 years, approximately. Now, I know what you're all thinking, especially those in the front row. There's no way that that guy up there has 40 years of work experience under his belt, right? All right. I see a few. Okay. All right. Thank you. Thank you for that. But to get more serious, I first wanna thank you for coming today. It's much appreciated. I'm gonna quickly take you through our global talent and delivery model that has evolved over the past few years, and why that evolution has made us stronger, more resilient, and better positioned than we've ever been in the history of the company to support our clients all over the world. Our delivery model today is not only stable, it's optimized. We've built a model that's more balanced, global, and flexible than ever before, and that foundation has been what's let us scale rapidly, move talent where we need it, move talent when we need it, and deliver for our clients no matter what in the heck is going on in the world around us, and we've had a lot going on in the world around us, as you all know. Now, I like threes, so there are three key takeaways that I'd like you all to take away today. First, we've successfully rebalanced our delivery base. The 2022 invasion of Ukraine was a catalyst, an unbelievable, almost unreal, incredible catalyst that accelerated our move into nearshore and offshore hubs without sacrificing client continuity and the quality of our delivery to our clients. Let me assure you can't learn that from the fine educational institutions that we have within a few miles from where we are today. You can only learn that by experiencing it, by living it, and that's what we did. Second, it wasn't just about moving people. It was about de-risking our entire delivery execution model, and we've built a rock-solid culture of resiliency. Resiliency first. Finally, we're now truly distributed around the world, harnessing the lessons that we've learned from crisis. Fortunately or unfortunately, crises have become a core competency of ours. It's helped us create a global engine that provides better access to top talent, and you've heard about the importance of top talent, and you'll hear about it today after me. This is now a durable competitive advantage for our enterprise. Now, to understand where we are today, you need to look at where we came from, where we started. Back a few years ago, in late 2021, we were already in the process of diversifying. As many of you that have followed us know, our footprint was still quite heavily concentrated. At that time, 59% of our delivery professionals, 52,000 strong at that time, were based in three countries, and you probably know them, Belarus, Ukraine and Russia. While this served us well for many, many years, it represented geographic concentration risk that we knew we absolutely had to address and deal with. Let's fast-forward now. A few months ago, the end of 2025. Look at the shift in the circles on the map here. Our delivery force has grown to almost 57,000 production professionals, but the distribution of where they are around the world is like night and day. We've reduced our concentration in Ukraine and Belarus by 38%, and at the same time, we aggressively ramped up other parts of the world like India, Latin America and Western and Central Asia. This is what optimized and balanced looks like. We're no longer dependent on any single geography, on any single region. We're much more regionally balanced and diversified today. Now, I'm extremely proud of how fast our teams pivoted. We have a saying that we use quite often around the place, "Speed kills when you don't have it." We had it, and we still do today more than ever. We relocated people, we opened up brand-new locations, we expanded our mobility programs, and we built talent pipelines in new markets, all at a pace that no other company could match. This speed and agility is absolutely part of the core of what and who EPAM is today. Today the model is a real strategic advantage for us. It helps us deploy the right skills to the right clients in the right places at the right times. It improves our cost positioning. It expands our access to top talent and gives us the geographic flexibility that is extremely difficult to replace. We're poised to capitalize on this more balanced footprint. We've de-risked our execution with stronger business continuity. We have better and faster talent access from a much wider pool of specialized and unique skills that our clients are demanding from us every day. As you'll hear from others, we're integrating AI-enabled optimizations across our company to improve our cost profile and utilization across the regions. Ultimately, the model that we're talking about here supports an important 24/7 or follow-the-sun delivery cycle, and that creates faster iterations and turns for our clients. Today, we find ourselves even faster, safer and more globally diversified than at any point in the company's history. Now, some of you may recall, the concluding comment that I made at these events in prior years, and I'm gonna say it again today, so it's okay if you don't recall. I'm gonna say it again today 'cause I believe it's more true now than it ever has been. We hold the cards that we've been dealt, and I wouldn't trade in our hand for anything. With that, I am excited and delighted to hand over to my good friend, my colleague, and frankly, one of the most talented and smartest leaders that I've had the privilege of working with in my 10 years at EPAM, Victor Dvorkin. Thank you very much. Thank you, Larry. Yeah, it will be hard for me to prove it. Good morning, everyone. I am with the company for 28 years, in the role for 10, and I will try to prove as a scientist that what we built is actually one of the best delivery engines in the industry, and that it will be actually rewarded by a native wave. Let's start. First, clearly enterprises got access to really powerful models right now. There is no doubt. What it means, that the demand for AI work will increase because they will understand better, they will want better, and they will ask us to do more. We spent the whole morning talking about enterprise complexity, legacy systems, complex platforms, integrations, hallucinations, we didn't talk about that, and real operating pressure which they have. This has been our environment for so many years. Large transformations, regulated industries, complex platform engineering, and also Google-scale product engineering at speed. This is actually how we won the digital wave in the past. Great models for us, in our opinion, is an opportunity because this is what makes our delivery engine actually unique, and that what will make AI run the enterprise. I will show you most probably one of the most complex slides, so bear with me. Larry spoke about our location strategy. Our location strategy is a serious advantage. I'm showing you an example of a large client. They have a headquarters in U.S., a headquarters in Europe, a local GCC, and a Latin American subsidiary. Think about the complexity. We have nearly unlimited flexibility how to configure this type of engagements, meeting the most strategic, regulatory, and pricing needs of our clients. We, as Sandra and Alexis said, we sense, develop, and deploy our talent. I will add, we also continuously assess our talent globally and unify our skills globally through global unified assessments. Every engineer, in order to get promoted, need to be assessed from an engineer actually to an SVP. We just finished the cycle right now. This consistency is a key. I will complicate the slide more. Data practice. As you see, it's global. It's in every location. This is our major strength, as well as cloud, digital and product engineering, SAP, Salesforce, and other practices. This horizontal capability is massive, with thousands of professionals, leadership, competency centers, partnership with cloud and platform providers, methods, tooling, training, certifications, and operations. I will complicate the picture more. I will add verticals. By the way, talking about hallucinations. In healthcare, they produce unsafe outputs. In financial services, non-compliant responses. In supply chain, the output looks great, but think about the world. It will not work today. That's why vertical is super important. That's why T-shaped talent matters the most for AI adoption. That's why organically, with our clients together and through acquisitions, we are continuing to develop vertical capability. Elaina and Eli spoke about consultants. I will talk about engineers. Think about healthcare, life sciences, financial services, media, gaming, more. T-shaped talent makes system work with AI. Think about now three deep pictures we just covered, right? It is absolutely unrealistic to run this manually. That's why for so many years we developed our digital ecosystem, covering talent, skills, knowledge, technology, and I will show you delivery. This is a delivery view of a delivery engine. See? It looks fine. Green. I actually would say it's a bit too much green. That's why we will drill down on a specific account. What we can see. Through AI-powered systems, we can now instantly understand what risk we are doing, what type of analysis we should have, and how to remediate the problem. This also accumulates our reusable delivery knowledge, which helps us with estimates and with many other things. The same view through the agent. You can see that agents and teams can query it from Claude Code or from other environment, or actually through the agentic factory. This is coming. The Vic bot. Yeah, it's me. I forgot the glasses. How to explain Vic bot? That's very easy. If you have a red project, Vc bot will come to you. That's how it was explained to me somewhere in the kitchen. Yeah. Most interesting, we both also work on our newly built AI factory, which we can demonstrate today. It helps to validate our proposals, it helps to check the estimates and the value we bring to our clients. With that, I will leave you with a few things for everybody. We have really advanced capabilities, global scale, consistent standards, T-shaped expertise, and AI-run platform which runs our delivery engine, which runs the enterprise, and which will be ready to win the AI wave. With that, actually, I have one more thing. To feel the organization's heartbeat, we prepared a panel with leaders building and running teams around EPAM. I would like to welcome Amit Singhal, Head of European Delivery, to introduce the panel. Thank you. Thank you, Vik. By the way, that big bot is real. It's calling me every day. It's much nicer him calling than Vik calling me. My name is Amit Singhal, SVP and Head of Delivery for EPAM in Europe. Joined EPAM roughly 10 years back, but who's counting? As Vik said, I'm gonna host a panel for you so you can hear from some of our regional leaders. Please join me in welcoming them. Okay. How are you all doing? Great. Very well. Yeah. Amazing. Okay. Sitting at the far end is Enver, my partner in crime in Europe. Hi. Hello. Maybe we should have sat together, but it's okay. Enver heads our business in Europe. By the way, congratulations on getting to the top place in Whitelane survey in Europe. Thank you. You and I both seeing an interesting trend in Europe where business is growing much more rapidly than we hope. We like it, but we had hoped. We do. Yeah. Across sectors and industries. Hope that's not an accident, and there is a strategy behind it. Keen to hear from you, what's going on there. Next to Enver is Srinivas, Srini, as we fondly call him. You and I joined roughly the same time in EPAM. That's right. Your mission was to build a different kind of India for EPAM, in the region and scale it. It's one of the largest location now, so you must have done something right, Srini. Yeah. Congratulations and welcome. Thank you. You took a long flight to get to Boston. I did. Through a narrow air corridor. That's right. Over Iran. Good. Martin. Hello. New kid on the block. Hi. Very new to EPAM leadership team. Martin, you were born in... Argentina. Argentina. You lived in Brazil and Mexico. Yep. You know the region a little bit. A little bit. You're enjoying your journey so far with EPAM? Very much. Okay. Just much like Srini, Martin joined us to consolidate our investment in the region and create one team which can be plugged into a global delivery model that Vik talked about. Welcome, Martin. Thank you. Last but not the least, Stepan. Stepan leads our teams in Ukraine, and all of us know, the war is still ongoing and everything that throws at Stephan and his team, and you continue to do good work. On behalf of entire EPAM family and our clients, Stepan, can I say thank you. Thank you very much. Thank you. Thanks for having me. Thank you. That's amazing. Thank you, all. Let's get into it. There's a lot to talk about, but let's try and focus on few things. I'm very keen to talk about resilience of EPAM delivery, how GenAI adoption is going across complex enterprises, how do we balance our global mindset, but equally, Srinivas, for example, in your case, working locally with GCC. Enver, if I could start with you. Sure. You and I know Europe is a melting pot of cultures and languages, and it's fragmented. There are complexities. How do you lean on big EPAM to deliver best-in-class services for them? Thank you, Amit. Indeed, Europe is a great mix of cultures and languages. A place from where a number of global companies are rooted. Also a significant market for a number of localized businesses. As Vik and Larry said, we as a company invested heavily into reinforcing our global delivery engine so we can serve clients from everywhere in the world. At the same time, working for a number of years with our clients, shoulder to shoulder, we accumulate a significant amount of industry knowledge. Today, I believe our winning combination is in-market Western European talents for client proximity, senior leadership and regulatory alignment. Eastern European teams or nearshore teams for in-depth engineering talent and for business knowledge, and offshore teams for technical talent for scale and cost-efficient execution. If you add on top of this, mature governance and now AI-powered productivity gains, then you get an engine which is both resilient and highly efficient. Right team supplied in the right proportions at the right time. Absolutely To the right situation is the winning combination. Martin, if I could come to you next. Bit similar to what Enver said, but we know Latin America is your backyard, so you know it better than the rest of us. What's your sort of winning combination in the region, both for your local customers, which you brought with you from Neoris, and plus EPAM global customers? Thank you, Amit. A pleasure to be here. It has been almost a year and a half since Neoris became part of EPAM, I think that due to that we have a much stronger EPAM in Iberoamérica. I'm glad to see that. The reason is that because we now have great engineers, plus all the AI platforms that EPAM build. Plus now we have a strong leadership team based in the region that know the region for a while. We also have a strong installed base of customers that were born in Latin America or they are playing in Latin America. As Larry, I like the threes, but I need to tell you four things, four avenues that we are pursuing in Latin America. The first one is the one that EPAM was pursuing since the beginning is how to supply or how to do near-shore from Latin America to the US, and that's something that we are continue growing and developing more capabilities. Those employees or those consultants are working with us are also gonna be able to serve our local customers in Latin America. The second avenue is how to bring those new technologies that we are building on a global basis to our install base in Latin America. We are very proud now to have, I say, the Navy SEALs that will help us to expand our presence in the region. We have the platforms. We surely need more of them. Yeah. This is something that we in the past story of Neoris we were not having. I'm very proud now we are. I think that we are gonna be very successful on bringing those things to Iberoamérica. The third avenue is that we also have global customers that we are having operations in Latin America, but we were not able to serve in the past. Now we are working with them. We are helping them to deploy those technologies in Latin America. You know that Brazil, for example, is a very complex country, and we do have an operation there, and we are getting to know them and expand that relation. Fourth, we also have a very established relationship with a lot of the large technological partners, and they were demanding and kind of how EPAM was able to go with them to the region. Now we are partnering with all of them, and I think that's gonna be another fourth avenue that we will explore in order to grow in the region. I'm very happy to see this combination as a winning one. Yeah. You said something very interesting that if you want to be resilient in the global world, one of the critical item is to have a strong leadership based locally. Okay, great. Stepan. Yes. I've got so many things I want to ask you, but time is limited. I can see it there. First of all, like, there is hardly a week goes by where I don't come across a customer who's been working with your teams in Ukraine, and all I hear is great words, and I know it's not just sympathy. On the other hand, when I talk to your people, I see motivation, I see high degree of engagement. What's the secret sauce? What's going on in the middle? Thank you, Amit. I think that's the most common question I get asked. First of all the credits should go to Ukrainian team. They are awesome, brave, resilient, and I'm really proud to be part of it. Now, answering your question, I think there are several components that help us to be successful. First and foremost, I believe that we secured the foundation. Basically, company stood with us from the day one. They created a $100 million dedicated fund to help our people, their family. You know, there is an expression, you want your employee to take care about your clients, take care about your employees, and that's exactly what we did. Second, I think we focus on the purpose, not the pity, and that might be not obvious for people outside Ukraine, but for Ukrainians, the biggest motivation is feeling yourself useful. You can protect country in trenches, or you can protect country on economic front. I remember a conversation with a client, like, who was kind of reluctant to open work for Ukrainian teams just out of a sympathy. Well, kind of, he told me, "Stephan, I cannot push your people to war during wartime." I told him, "Well, while I appreciate your heart, but the truth is that our people has a tremendous motivation to work because it brings revenue, it increases taxes, you know, it helps to protect, like, working places, IT industry, et cetera. That purpose gives our people control while kind of everything else is volatile. He was like, "Whoa, I didn't think about that from that angle." That was eye-opener for him. He opened, like, work for our teams, and they've been delivering for him ever since. Last but not least, I believe it's our results relentlessly attitude. You know, London Stock Exchange, our huge client. They have a massive, like, program of migrating hundreds of applications from on-prem to Azure. By the way, like, several previous attempts failed with other vendors. Just recently, we completed a first migration of the application that was done by a small Ukrainian team with a little bit of a sleepless nights, of course, with the usage of AI. It was done on budget, on time, and client feedback was that it was the most seamless migration ever in his career. At the end of the day, while the environment may be volatile, we've proven that our delivery is a constant thing. We don't just meet the standard. I hope that we set the new one that could be called resilient partnership. No, it's absolutely. I mean, it's. I see this every time we having client conversation about Ukraine. As you said, if you wanna help Ukraine, work with us. Great. Thank you. Thank you, Stepan. Quick follow-up. One other interesting thing we saw in Ukraine was very early adoption of GenAI. In fact, some of the EPAM IP, like CodeMie and ELITEA, was born in Ukraine, which became part of EPAM AI/RUN platform. Again, what was sort of the driving force behind it? Well, great question, Amit. In order to understand like how it happened, you have to understand Ukrainian engineering DNA. To be honest, we always been very fast adapters of everything new. Look at our Ministry of Digital Transformation, our Diia mobile app with the government in the mobile, with all the document services, defense tech, nearly cashless society. For us, like AI is not a hype, it's a kind of skin in the game. If we don't disrupt ourself, we're not gonna win. We're not gonna be successful in front of the clients. Yes, indeed, both tools, CodeMie and ELITEA, which are part of AI/RUN platform that Adam and Dima was talking about, was born in Ukraine and by Ukrainians, which basically proves that we not just like deliver despite all the adversities, but we also innovate. Yes, we see a shift in the engineering role from kind of how, which is code generation to a certain extent, to what and why which is focusing on complex, like client's challenges. Here is an example from real life. Vadim, who is a product manager of the CodeMie, it's an AI-native agentic platform. He was doing a demo, and during the demo app crashed. Instead of just panicking, he just like went to CodeMie agent and described the bug and asked agent to fix it, run the test, and deploy to production. We went for a 10-minute coffee break, returned back, and boom, it's already fixed and in production. Like Boris from Anthropic said, Claude is coding Claude. Exactly CodeMie is coding code. Exactly. It's amazing. Amazing story. That is exactly the level of maturity we bring to our clients. It's not just about code snippets generation, it's about automations, the full cycle of software development. At the end of the day, we believe that AI is a multiplier for human brilliance. Given all the components we have and our strong engineering DNA, we believe that we're gonna remain steady, innovative partner that our client trust to continue solving their complex challenges. That sounds amazing, Stepan. As you said, if you wanna win, you have to disrupt yourself first. Exactly. It's great. Thank you. Srini. Yes, Amit. We should talk about India. Yeah. Not about the pollution and traffic and the population, but EPAM India. EPAM. It became the largest location in EPAM in a span of what? 10 years or so, roughly? That's right. Clients tell us, and we see it ourselves, but clients tell us, which is probably a bigger proof point, that it's very different when they work with EPAM India versus the rest of the competition. What's behind the scenes story? How did you go about doing it? What's really different? Thank you, Amit. I think we differentiated ourself in the India market by building a modern engineering company. It was built on our EPAM's global engineering culture and hiring quality talent. We did this over 10 years, and we did this very differently. Today I have very senior leadership teams in India that manage mature practices in cloud, in data, in data science, and now in AI and GenAI. Local is strong leadership. Absolutely is critical. I remember the first global AI workshop was conducted in Hyderabad. This was for a week, more than 2.5 years ago. We have all our senior AI leaders in Hyderabad, and most of them are actually in this room today. When we were done, one of the OKRs that we came out was to make EPAM India the first AI-native location in EPAM. That, for us, really started with training our engineers. Today our AI literacy in EPAM India is 90%+. More than 70% of our projects leverage AI tooling, either our AI-run or some agentic AI that is provided by our client. In addition to that, the teams in India have also contributed to our AI initiatives. We built the AIOps platform that we leverage on all our managed services engagements. Which is now part of EPAM AI/RUN bigger platform. That's right. umbrella. That's right. Yeah. We also built an AI reverse engineering tool and agentic swarms for use on our modernization projects, right? If you think about it, some of EPAM's largest implementation on CodeMie, on ELITEA, on Claude Code, are being run out of programs in India today. Yeah. No, we see that. We see AI adoption at scale with large enterprise in India, so well done. Thank you, Srinivas. Thank you. Quick follow-up. Yeah. Again, being the largest location, you play a very big role in EPAM's geographic diversification for U.S. customers, European customers all over the world. You have the other side of the coin as well, which is GCCs, which are rapidly coming up and building in India. Could you talk a little bit about it? Do you think GCC is a big opportunity for EPAM? Yeah, a good question, Amit. As you're aware, we today work with 150+ clients in India, and we work with them in various different delivery models. The traditional outsourcing where the teams are exclusively based in India and hybrid, and we do quite a bit of work today in the hybrid model where we have teams in India, but we also have teams in one or multiple of the other locations. And like you said, in the local market, we work with those global capability centers or GCCs. Today, we work with somewhere between 50-60 GCCs in India, and we've been working with them for more than 10 years. And over those 10 years we've built strong local relationships and today, I think in most of them we are their trusted partner. I think that's happened mostly because of our advanced engineering skills, our AI capabilities, which really complements what the GCCs themselves are looking to build in India. The answer to your question is yes, Amit. I think their rapid growth over the last few years in India is actually an opportunity for us. Premium skills and proximity to GCC is. That's right. is what they're looking for, and- Yeah sounds like we're winning there. Yeah. No pressure. Thank you. Okay. Before we wrap up, there is one big question we have to sort of talk about, which is we see, and the industry is talking a lot about it, there are a lot of large complex enterprise clients are stuck in this R&D and POC phase and not really able to scale GenAI into their environment. We have seen some early success with these organizations, so can I ask both you and Martin to share some examples where you believe that we managed to unlock the key? With pleasure. Yeah. Martin, would you like me to start? Okay. Okay. Yeah, indeed. Clients are quite excited and to certain extent under pressure, as you rightly said, and they run multiple POCs in the last couple of years, and now they really get to see real implementations with real returns of the investments. I believe opportunity is big and EPAM is very well positioned to capture it. The key arguments for this are, as you all heard, our top-notch technology excellence. Second is industry knowledge accumulated over the years, and third is our early and very practical investment into AI. All of this helped us to form very concrete industry aligned points of view on how AI and modern platforms can transform our clients' businesses. Importantly, we didn't stay on PowerPoint levels. We went all the way and implemented industry specific accelerators and our clients use it nowadays. Just to give you a couple of examples. First one was Swiss Re. They used to produce sigma report, very well known in the industry. We helped Swiss Re to ideate, validate and deliver Sigma Explorer, something that connects all resources, all publications, all data sets, and helps end users to talk to the data, do the data analytics using the natural language. We developed the system using two EPAM accelerators, DIAL and QuantHub, and it went live in a very short period of time. Another very important example is gonna be 1&1 or how they call it in Germany, 1&1, major German telco. They wanted to reimagine the way how they interact with their users. We developed for them an agentic AI platform that today handles hundreds of thousands of end user calls. Not only helped to cut operational costs, but it improved the client satisfaction level. We used our AI/RUN transform platform to develop it, and the first agents went live just within several months. Sounds like we need to say good luck to our friends who are running traditional BPO industry. I will do this. Okay. Martin? I have three examples of Latin America, and this is in Latin America. One is, there's a large utility company in Brazil that is doing a big migration from a legacy system into SAP on the cloud, and there is a big need to migrate tons of data. At the same time, they are going through an M&A strategy towards acquiring companies in the region. They were thinking about how to do it. We were competing with some of the local competitors, and they were going for more the traditional approach of migrating data. We came with AI/RUN and migVisor as one of the platforms that we have. We've been able to prove them that by using this platform, we are gonna be not just able to do it faster in the first time, but also have a repeatable agent that will help later in the future acquisition. That's one of the first cases, and it's very interesting. The second one is like we have a large manufacturing company in Latin America where it's having like cameras to surveillance the plants. Not for spying. Eh? Not for spying. Not for spying, but at the end, we transform those cameras into a living agent that is serving what's going on. Now we are able to track all the tractor into the plant and foresee what they are doing and optimize their routes. We're also monitoring inventories, and we are helping them with health and safety in terms of seeing if the people are in the right places, they are using their helmets and the like. That was a physical platform that was there without taking the value. We explore that. Last but not least, in terms of agentic, we also implemented an agentic platform in one of our customers that is in the bakery industry to help them to better serve their suppliers and give them information of where their payments were, if there was something that it was blocking, when to expect those payments to happen. That allows them to reduce like 30% of their physical agents and it's kind of case of the BPO that you werehey were mentioning. I think sounds like based on examples both of you said is it's a combination of industry depth, good old EPAM engineering, but applied in a forward deployed capacity to work with clients closely. That's great. Thank you. Thank you. Thank you. Thank you, Amit. Martin and Enver for sharing cool examples. Thank you Srini and Stepaan for what you do. Thank you. How you do. Between two of you, we have good part of EPAM, so no pressure again. Sounds like resilience by design. We need more of it. Thank you all, and that's a wrap. Thank you. Next you're gonna hear from our CFO, Jason Peterson. Before Jason comes on the stage, again, let's hear from one of the EPAM clients. They're called Louis Dreyfus Company, one of the largest global commodity trading, soft commodity trading company and logistics company. Enjoy the video, and then you'll hear from Jason. Thank you. It's great to be here with you today. I'm Guy-Laurent Arpino, and I serve as Chief Information Officer at Louis Dreyfus Company or LDC, which is one of the world's leading global merchants and processors of agricultural goods since 1851. I oversee our global digital strategy and technology initiatives spanning trading, supply chains, and corporate functions. I've been part of LDC for 10 years, following 15 years at Procter & Gamble and 5 years at Bacardi. We began working with EPAM in 2019 on our analytics and BI transformation, quickly scaling teams across Hungary and Belarus. The partnership expanded naturally into software engineering with projects such as My LDC, our customer portal, and our largest front office program. Throughout COVID and various geopolitical disruptions, EPAM has ensured delivery continuity and helped us scale effectively. They also executed the award-winning migration of our five global data centers to Microsoft Azure in just 24 months. More recently, we've partnered on strategic AI initiatives, including next generation pricing engines. What truly differentiates the relationship is our shared focus, not only on what we built but how we built it, ensuring scalable, sustainable, and modern engineering practices in a fast-evolving landscape. Today, we jointly embark on fully leveraging the potential of agentic AI software development life cycle, transforming the way IT solutions are being designed, implemented, and delivered at scale. This will allow us to achieve our ambitious roadmap to become an AI-powered company. Over the years, EPAM has played a significant role in modernizing the application landscape, enhancing our enterprise architecture, and reducing technical debt by approximately 40%. In addition, we've made substantial progress in our data estate, developing a data platform on Microsoft Azure from the ground up. This platform serves as the cornerstone for both our data and science initiatives and AI-based products and services. We anticipate further opportunities for collaboration and innovation and AI-enabled software development. I can only advise you to keep the high degree of ownership and accountability in the delivery of our projects, and I look forward to benefiting from the broader perspective across industries and the technological landscape, particularly around AI. In this final presentation of the day before EPAM's closing remarks, it's probably gonna be no surprise that I'm gonna talk about the business from more of a financial perspective. I'm also gonna lay out our expectations for the coming three years, 2026, 2027, and 2028. I'm gonna focus on our accelerating revenue growth. I'm also gonna talk about our improving profitability, and then I'm gonna talk about our ability to continue to generate strong free cash flows. First, I wanna explain kind of what's in this slide. Off to the left, clearly it's 2022 through 2025 are actuals. For 2026, what I'm showing you is just the midpoint of the guided range from our most recent February earnings call. You know, I think the point that I wanna make, and I think Larry did a really good job of kind of reminding us kind of what we've been through over the last four to five years, is that, you know, we had to deal with increasing sort of difficulty in our operations in Belarus. We had the invasion of Ukraine. We exited Russia. That was both a delivery location, and it was also a revenue generation, revenue-generating market for the company. We were able to maintain steady revenues throughout this time period, returning to growth at the end of 2024. Further improving our growth rate in 2025, where we recently discussed our organic constant currency growth rate of approximately 5%. More recently, discussed our expectations for 2026 with a 3%-6% organic constant currency growth rate. If I look over to the profitability side, from a non-GAAP operating income standpoint, you know, we're nothing if not adaptable. Again, what we've been through with having to move our populations, support our employees, make certain that we've maintained our customer commitments, continue to invest significantly in capabilities, particularly all the AI capabilities we've been talking about. We're able to maintain sort of steady non-GAAP operating income throughout the time period, again returning to growth in 2024, further accelerating that growth in 2025. We're talking about solid growth as we move from 2025 to 2026. Off to the far right with the non-GAAP diluted EPS, again, you've had growth throughout the last three years. For 2026, including the share repurchases, we actually return to double-digit growth in non-GAAP EPS between 2025 and 2026. I think this is a really interesting, and you've seen this kinda throughout the day. Why it's interesting to me is that not only is our expanded geographic footprint a source of revenue growth for the company, but it's also an opportunity for us to continue to expand profitability. I think we've talked about the fact that, you know, we really have delivery excellence regardless of geography. We've got AI capabilities globally in all of the regions in which we operate. You know, what we'd understand then is that, of course, now instead of just delivering from Belarus, Ukraine, and Russia, we now have the opportunity to deliver around the globe. We can meet client expectations for different time zones, different price points, and when clients have specific sort of preferences in terms of geography. Now on top of that, let's talk about profitability. You know, I think what everyone would understand is when the invasion of Ukraine happened, the exit from Russia, we had to move quickly. We had to move into new countries. We had to grow rapidly. Okay. The net result was that we were taking care of our employees. We're meeting our client expectations for delivery. At the same time, we were growing and then obviously focused on cost efficiency, but it was a lower priority. Okay. Today, we've been much more focused on cost efficiency in some of the newer geographies and the geographies that scaled quickly. I think I've been saying for the last couple years that, you know, even if you're worried about bill rates in India, we can still maintain high levels of profitability there and that India actually generates higher profitability than the company average. If you add to that the fact that we've been focused on the cost efficiency, India continues to improve profitability, and the gap between India profitability and EPAM average profitability continues to grow. We've done similar things in Western Central Asia, where we've continued to grow our profitability. LatAm has been interesting because, you know, one of the advantages of the Neoris acquisition is we've learned a lot more about how to operate efficiently in Colombia and more recently in Argentina. In all these cases, this gives us a further opportunity to sort of improve our profitability. It's one of the reasons why we're guiding towards profitable revenue growth in 2026 with an expansion in gross margin. This is effectively just a reiteration of guidance, right? It's $1.385 billion-$1.4 billion for Q1. For the full year, 4.5%-7.5%, which digests down to 3%-6% organic constant currency growth. What you'll note for the non-GAAP income from operations measured as a percent of revenue is that the 13.5%-14.5% for Q1, okay, at the midpoint is higher than what we generated in Q1 of 2025. The same thing's true for the full year 2026. The midpoint of the 15%-16% range, again, higher than what we actually produced in 2025. We're seeing not only revenue growth, but improving profitability. Again, you go to the bottom portion of this page here, and you add the addition of the share repurchases, and you've got double-digit growth in non-GAAP diluted EPS, approximately 14% in Q1 and at the midpoint of the range, approximately 11% for the full year. From a long-term financial algorithm, you know, what you're really looking at is a focus on continuing to grow and to accelerate that growth through success in the market for AI native and AI foundational services. We're looking to continue to expand profitability. Again, that'll be with a focus on sort of cost efficiency. We've all talked about AI productivity and the opportunity to share those benefits with clients, give them some cost efficiency, retain some for ourselves, which improves gross margin. We've always had strong operating cash flows, modest capital expenditures, so that produces strong free cash flow. From a capital allocation standpoint, we continue to invest in our business, we've done strategic M&A, and more recently, we've introduced share repurchases, including the $300 million ASR that was announced in March of this year. From a growth standpoint, I think, you know, what I'd first do is take you off to the right side of the page. You know, we are participating in an immense $1.8 trillion IT services market. Again, we're quoting the Gartner statistics. That market is growing. Underneath or within that market, there's the much higher growth opportunities associated with AI native, AI foundational, and then we've talked off and on throughout the day about kind of the more greenfield opportunities for EPAM, agentic BPO, AI-enabled managed services. There'll probably be some contribution from M&A over time. What we are looking to do is continue to accelerate our revenue growth by participating and, more importantly, succeeding in the high-growth markets. With a goal of eventually returning to 10% or a double-digit organic constant currency revenue growth. From a profitability standpoint, you know, I've talked about the fact that we were from an actual standpoint in 2025, 15.2% adjusted IFO. As you move to 2026, you've got the guided range of 15%-16%. What we're looking to do is continue to improve profitability over the next couple of years. Returning to a 16%+ in 2028. Again, what we'd be focused on is both improving gross margins and then in 2027 and 2028, also gaining some additional benefit from SG&A. I think I've talked over the last couple of quarters about our focus right now is to continue to invest in business development and sort of sales-focused marketing. I don't expect us to see a lot of leverage in SG&A in 2026. Instead, what you'll see, gross margin expansion. Then over time, you'll see a little bit more efficiency benefit from SG&A. At the same time, you know, we're focused on generating between 50 and 70 basis points gross margin improvement. After 2026, that would come from the cost efficiencies, that would come from the pyramid or seniority index we've talked about. Nothing heroic, just kinda returning back in the direction of what we might have generated historically. Utilization improvement and then the AI associated benefits, again, sharing those with our clients. From a free cash flow generation standpoint, we've always had strong free cash flows or generated strong free cash flows, over $500 million in 2023, over $500 million in 2024. More recently, we actually generated over $600 million in 2026. As I look forward, you know, we'd be committed to continuing to maintain the 80%-90% conversion rate that we have historically targeted. As I look at our financials over time, that means we would generate over $1.8 billion plus in free cash flows over the time period 2026 through 2028. I think most of us are aware of the fact that the company's got a very strong balance sheet. At the end of 2025, we had $1.3 billion in cash. We have modest debt. We have a untapped credit facility. On top of that, we've got the ability to generate the $1.8 billion in free cash flows that I talked about. As we look over the last couple of years, our historic use of cash clearly we invest in our business. I think we've talked about this throughout today, right, in terms of the skill development, the education, the platform technologies, the AI capabilities, the IP and the assets. We're spending hundreds of millions of dollars on that. That keeps us at the cutting edge and gives us the opportunity to continue to grow faster than the rest of the market. We'll continue to make those investments. We'll continue to do strategic acquisitions. Then over the last couple of years, we also introduced share repurchases. We would continue to do those. Off to the right here, we'll continue to reinvest in the business. You'll have capital returns in the form of share repurchases and of the $1 billion that was authorized. Most recently, we still have $450 million left in that. Finally, you'd continue to see some level of M&A, probably more in the tuck-in category in 2026. If I then just sort of close here on the M&A objectives, you know, we clearly would look to sort of expand our in-market capabilities, particularly, industry vertical capabilities, and clearly that augments our AI capabilities. We also might use M&A to help us, you know, effectively be an entry point for select geographies. This is the type of idea where you sort of create a beachhead, which then you can grow behind. Finally, we would use M&A to sort of deepen the scale of certain high-growth capabilities. I've always thought of our M&A strategy as one that is not necessarily designed to buy revenue, but it's really designed to sort of help shift the company, to create an opportunity for the company to address different opportunities and then further our organic constant currency growth rate. Most of the companies we acquire do have our services businesses, so there's strong free cash flows. Finally, our historic focus has been to make certain that we're able to sort of maintain the 16%+ profitability. Over the last couple of years, we got away from that. In the future, what you'd see is we'd make certain that we did acquisitions that allowed us to either achieve the 16% or actually sort of facilitated the achievement of the 16% profitability range. In conclusion, we're focused on ongoing acceleration in revenue growth. We intend to continue to improve profitability, returning to the 16%+ adjusted IFO level by 2028. We're gonna continue to generate strong free cash flows, the $1.8 billion+ that I've been talking about. We'll continue to make disciplined capital allocations, including share repurchases. Again, with that's the end of my presentation. We are gonna have Q&A after this, but right now we've got one more customer video. I think it's Bank of Ireland, and thank you very much. Hi, I'm Myles O'Grady, Chief Executive of Bank of Ireland Group. I want to share the story about our new app, which EPAM has strongly supported us on, launching in the coming months. As we all know, customer expectations have changed fast and continue to evolve at pace. Keeping up isn't enough. We need to ensure our technology is market-leading. We've implemented change and made improvements with increasing momentum. We've upgraded systems across the bank, delivering greater stability and resilience and better customer service. We've invested in technology that our customers use most, facilitating payments across Europe in seconds and upgrading our digital banking offering. AI has helped us protect customers more and do things faster and better. A core focus has also been the reinvention of our mobile banking app, a hugely important part of customer service offering. We have been working closely with EPAM on this, and I know they understand our vision and ambition for what we want to deliver here. The result is a banking app in pilot right now and launching soon that we can be proud of, that will deliver great outcomes every day for our customers, and will help us go further, faster over the time ahead. 2025 was a transformational year for Bank of Ireland in our tech delivery, and this year promises to be even more exciting. I'd like to thank FB, Arc, and all the team at EPAM for their strong support in the progress we are making and in the delivery of our ambitious plans for the future. We're looking forward to the journey ahead and to what we can achieve together. Okay. A lot of content today. We've got our final Q&A session with several of our leaders. Same rules as the first session, so please raise your hand if you have a question. Allow the mic to come to you. Raise your hand. Excuse me. State your name and firm. For those online, if you submit a question, we are looking, we'll field those as well. Let's go with the first question right here. The glasses. Thank you. Yeah. Thanks. It's David Grossman from Stifel. You know, you did a great job of laying out the structural tailwinds from AI and why EPAM is well-positioned, you know, to benefit from those tailwinds. I think what's notable is, you know, historically at least, these massive changes in technology have been accompanied by accelerating growth for the industry. On the other hand, industry growth has been relatively low, you know, call it the last 18-24 months. In your opinion, what is so different structurally about this cycle, and what needs to happen for growth to not only re-accelerate for the industry, but obviously for EPAM as well? David, good to see you, let me try to address that. I think what's really different at this time is the rate of change of these fundamental technologies are so much faster. Our clients, ourselves, and everybody who is participating in this is just watching the race, what we are seeing. It's what somebody in the audience we discussed it already this morning, that some people are just waiting till things gets cheaper, right? They are waiting for if you wait one more month, maybe the model will get better. Maybe if you wait one more month, maybe the model not just gets better, it gets cheaper. Just probably six months ago, when we reached the point where the model's results are good enough and they're cheap enough that you actually can launch these transformational programs. I think we got so accustomed to that people rush ahead and allocate capital and start making these investments that we underestimate the resistance and the time and cautiousness people are having with these new AI models, because it's no longer just an IT change. Cloud was the internal affairs of the IT department. This is a business change. This requires business leader committing to a massive change program, how to change the whole business processes, and also addressing the technical debt which they're carrying today. Because without addressing the foundational element of AI, which we keep talking about it, the cloud migration, the data and data product creation, the legacy modernization, you're not going to get the benefits. You need to upskill your teams. Everybody's reluctant to get locked in to a vendor, locked into an engagement model, and everybody's hoping that they can do this without massive changes to their organization. This has created kind of, I would say, a wait-and-see period. Now what we are feeling that organizations are no longer able to wait longer. They are just ready to launch into it, and we have these active discussions, which makes us very optimistic that going forward we're going to see the demand bouncing back. Now, when do we see it for the whole industry to start doing that? When one player, one client of ours or maybe a client of our competitors actually succeed with the transformation. One Maybe they don't even have to do the full-blown transformation of a whole company, but if you transform just one line of a business and achieve some level of efficiency gains or speed to the market, which we never seen before, that will force everybody else in that vertical, in that geography to do the same and do transformation en masse. I think this is where we are, and we are in this tipping point. This is the first time when you start hearing from the frontier players, the Anthropic, the OpenAI, that they actually done the engineering and they actually now seeing that the first time he really saw real efficiency gains from software engineering using AI, something which really surprising. The first time he actually trusted the AI to do the coding was late last year. I think we just underestimated how much time it will take to get to this stage, and we are there. Now it's going to start happening. Maybe in the back. Great. Hi. Oh, yeah. Thank you so much. Hi, Maggie Nolan with William Blair. Why is vertical expertise more important now? EPAM has a broad set of verticals that they address. Do you need to narrow that focus, or are there ones that you're going to start with first to maximize success? Maggie, good to see you, and I think it's a good question. Why now? In the digital transformation space, horizontal skill sets were much more important. People were actually applying horizontal capabilities into variety of industries. During the AI transformation, on the other hand, they have to solve business problems. They have to now tackle the business challenges. That requires real industry knowledge. That requires you to discover how to automate that piece of functionality. That requires you to really understand deeply what to do. You can walk around and you will see how we are tackling it in energy, how we're doing it in healthcare, life sciences. In order to do that, you really need to understand what you're doing because as Vic mentioned, the models will hallucinate. If you're not grounding it into vertical expertise, what you're going to produce is not going to be safe. If you look at LivaNova case study, which is an AI engineering case study, the fact that they've got their software FDA approved, and by the way, we used a ton of agentic solutions, it underlines what you need to bring to the table in order to make it safe, in order to make it really productive in this environment. Vic, Elaina, do you want to add something to it? I think the cycle change that we see is broadly a move from digitizing businesses, which is what we've been doing for the past 10 years, you know, with cloud and modernization, to transforming them. I know we've been using digital transformation kind of as an industry term. I think we're really on the forefront of actual business transformation. It's not just digitizing or creating data platforms. It's actually reimagining new business models with an AI-centric point of view. That's hard technically hard, but it's even more difficult from an industry point of view because particularly in regulated industries, you don't just get to try it and see if it sticks. Maybe one more thing. We have actually we are not starting from scratch. Like, from 2014 or 2015, we are building healthcare and life science at scale of the whole organization end to end. You will see Greg today, he will see it and show it, and it's engineering, it's consulting, it's advisory strategy in all the levels. It's a good question about focusing, but we are doing it, and so it's improvement. It's not necessarily you need to be locked in somewhere. The same happening with energy from 2016, from large workloads there, and so time after time, gaming. You see it with us actually over time. Let's go here. Surinder Thind with Jefferies. As you think about the build part of the equation and you start to build bigger and more complex platforms and all of the orchestration that's going to be on top of that in terms of the agents, who at the end of the day owns the IP, and do you have the ability to maybe manage or run those platforms and monetize the agents or the capabilities, or does EPAM still remain within the build part, and then you just kind of let your clients run the platforms at that point? I don't want to say you walk away, but then you work on the next project. Thank you very much. I think it's hard to see where this leads to. I think we're already in the position that the build versus buy equation is flipping. We are starting to build more, and the clients are choosing to build more instead of buying off-the-shelf packages or SaaS solutions. We are actually rebuilding some of these SaaS solutions for the clients to take it in-house. In the current wave, what we're seeing is that people want to own their own IP, especially when you are talking about agents. Remember, this is a workforce transformation. You want to own your own workforce. Even if your workforce is no longer humans, they could be agents. You as an organization, you have to risk mitigate. You are dependent on your workforce. We are seeing clients really want to own the agents themselves. They want to have flexibility. This is at the next level of risk management. You cannot be locked into a vendor like EPAM or even to a model or even to hyperscalers because now your whole business starts dependent on that workforce. I think we have to start seeing this transformation itself in a very different eye. We have to see it as a workforce or actually whole business transformation and less on IT transformation. Once you start seeing it from that angle, I had these discussions just the other week with an insurer. They are seeing this from a risk management point of view. Who owns the agent itself? In the end of the transformation, they're letting go their original workforce, and now they are relying on a new agentic workforce. I mean, that equation, your business dependency is switching, and they wanna own that dependency. Can I just? Yes. There's not just the IP over the build versus buy. The critical sort of rights issue is to the data, and it actually is probably one of the reasons why, you know, the frontier companies will likely not end up owning the full end-to-end because there is a critical mission type of not just rules and logic, but actually the ownership over their own data. Yes, we can maybe operate some of the platforms that we design and build, but it would be a rare thing where we would be the owners and controllers of the underlying enterprise data set. Let's go here. Hi. Phani Kanumuri from HSBC. As you said, the technology is evolving very rapidly, so how do you ensure that your employees are upskill in such a fast-changing technology? And how do you price in this technology? As AI native services likely requires a long contract period, so how do you price in these kind of changes? That's a very interesting question. I think we already saw in this AI transformation space probably two or three technology shifts by this point, right? I do remember when Andrei Zahorodniuk very proudly launched the next generation AI architecture, which is probably six or eight months later was out of date. I don't know if you remember the RAG architectures and all the different vector databases, which everybody was crazy about probably 18 months ago, 12 months ago. Today, nobody talks about it anymore because the context window grows so much. I think staying on the frontier is requires you to continuously do R&D, continuously have people who are on the frontier and actually on the edge of the model. We have team members working evaluating, building new types of capabilities, in-house, and from that, designing new types of educational programs. The educational programs which Sandra and Alexei was talking about, how we pushing it out. I think Vic was also indicating that we codified the environment which we are operating. In reality, we are running the internal systems with agents, with MCP connections to the internal application, so you can actually run operations as a code in the organization. This is a very different shift. But how you educating them continuously, how you are actually making them work continuously, we're running program. Maybe Larry or Vic wanna talk about this. Yeah. Just the one thing I was gonna add is, to some degree, a lot of this starts from the beginning, from the selection, and we have very, very rigorous technical requirements and expertise that comes from EPAM that starts even before the individual joins the company. We try to only include in that pipeline of candidates that we select those that we believe have the strongest technical chops. Just to continue on this. This is very important comment because one of the key differentiators of the AI agentic engineers is judgment. We actually continuously, and this is what Arkadiy Dobkin started to say, we were selecting people with judgment all the time, maybe subconsciously, maybe consciously, but now we understand exactly how to select them, how to separate those who have it, those who do not have it. Dmitry had a great message on talent density. Those are important building blocks. Now, about the speed and desire and everything, it's all about also top-down by example. If he's coding, I'm coding. We can demonstrate it. We can show it. The next managers will be coding with Claude Code, with something else, and this will stimulate newer technologies. We also have mandatory requirements for education. If you are not educating, it's a bit of a problem. Now, going back to the pricing, which I think was your underlying question, seeing where you're sitting and what your role is. I think we are clearly, for this type of skills, we are able to charge higher rates, which actually we talked about it before, that our AI native portfolio drives higher margin. I think it's a continuous moving target because some of these skill sets becoming commodity and as technology rapidly changes. Let's go here, and then we'll go there. Hi, it's Bryan Keane at Citi. Maybe for Larry and Victor, how do you imagine the delivery model in terms of people? Do you need more or less as this evolves over the next three years? Just one for Jason, you know, accelerating revenue growth, given the industry dynamics right now, the question obviously is on visibility. You know, what kind of comfort can you give us in visibility, either contract bookings or when you look out two years, you know, what percentage do you see and how do you get to that number of accelerating revenue growth? Thanks. Yeah, I can start by saying on the more or less, I think the answer is yes, it's both. I think in not only from a geographic perspective, but from a skill set perspective, more of some of these, less of some of those. If you go back to recalling some of the things that Sandra was talking about, the level of data and the signals and the metrics that we track in order to figure out as best we can where we need those people, what skills helps us get a little bit ahead of that curve. I think the other thing that I would say is, you know, we work really hard to put a plan in place every year, and my view is it's only valid for one day, January first. Because on January second, something has already changed, especially in the market that we're in today and the companies that are gonna win are the ones that can figure that out and pivot the fastest. For the accelerating revenue, first I'd just start with this year, 2026. With the guide at 3%-6% organic constant currency, you know, our focus is on making certain we can at least hit the midpoint of the range, and clearly we're all driving to achieve something to the higher end of that range. There's already kinda line of sight to larger opportunities that if we can close, and we're trying to close, I think sorta drives us above that midpoint of the range. As I look further ahead, it's the ongoing success with clients. It's all the things we've talked about that clients can't do this themselves. They're increasing dependency on partners like EPAM, but hopefully what we've convinced you of today that this isn't easy and EPAM is extremely well-positioned to participate in these high-growth market opportunities. If you can be successful in a market that's growing rapidly, that drives higher revenue growth, and that's kinda how I would think about it over the next couple years. We have time for one more question. Let's go here. Oh. Thanks for the presentation. Puneet from JP Morgan. It was interesting to see, like, all those, like, the regional heads coming here, like, on the same table in the panel. Talk to us, like, how does EPAM operate across different regions? Is it like? Because, like, the individual regions might have different cultures, like, the policies. Like, is it the same culture, same EPAM across everywhere, same type of people, like, in terms of profile type of people you hire across all regions, or are there differences based on that region's policies or culture? Let me try to start with it. You know, Victor is running a global delivery platform. Basically, he runs the factory itself, right? It's an engine. In this engine, we are enforcing certain level of uniformity, right? What Victor highlighted is the assessment, and basically that's all requirements, how you're going to get promoted. That's the way you are actually being assessed. That's the way you are actually reaching the next level. Is it the same culture? No, because we are coming from different parts of the world. There are unifying elements. There are values which we are sharing. There are ways how we're communicating, and we have to collaborate. We have to work together. We are working together to deliver to one client. Throughout this delivery, we actually kinda syncing up. We have the same values what we're pushing out. We are assessing people in the same way. We're hiring for the same goals and for same profiles with the same criteria. We're running the same process globally, how we run compensation, how we run assessments, how we're going to provide feedback and performance management. It creates one level of sync. Overall, we're hiring engineers, and engineers kinda understand each other and kinda sync on it in a weird way, right? In a geeky way. I think that's who we are. If I could just add on. Absolutely. Sorry. Go ahead. Were you done? No, exactly. Go ahead. No, go ahead. Go ahead. Go ahead, Larry. I think a short way to look at it is globally consistent, locally relevant, and at the end of the day, it's what's best for the client. Client-centric decisions that are locally relevant with the global consistency in processes, culture, core values, but locally relevant is extremely important. Appreciate it. Excellent. Thank you. That wraps our Q&A session. I'm gonna hand it back over to FB for closing. If we figure out where the clicker left the building. Who has the clicker? All right. I hope, by this point with the team, we made clear our positioning and why we have the right to win in the AI-native era. I really would like to thank the team itself to make such a great presentation and actually present this message. Our people have navigated technology, social, and geopolitical challenges and changes. We have emerged stronger out of it. We learned a lot, and I think we are the most resilient organization out there, not just in terms of against geopolitics, but any type of technology and social change. Why invest in EPAM? We will be the winners in AI era. We are best positioned to be a leader for enterprise AI transformation. We have the strongest engineering talent or engineering DNA in the industry with a track record of solving our clients' most complex, hairiest problems. We are delivering already AI foundational and AI native work, and it's expanding, and it's growing significantly. We have a clear strategy focused on accelerating and driving profitable growth with margin expansion. Our 2028 goals are accelerated revenue growth, 16%+ non-GAAP operating income margin, and delivering $1.8 billion cumulative free cash flow throughout 2028. Thank you very much. Okay, it doesn't work. As I said to you, the something has to break. Thank you very much for coming. For the audience online, we would like to thank you for attending, and see you next time. Thank you.

Speaker 24: Good morning, everyone. Thank you for joining us today. I'm Mike Rowshandel, Head of Investor Relations. Whether you're joining us live here in Boston or dialed in through the webcast, we appreciate you joining us today. We've been planning and preparing for this day for quite some time now, and I can tell you the energy in the backstage is buzzing. Our entire leadership team is here, eager to take you inside our story, what we've built over the past three decades, and more importantly, the how and why we're positioned to be successful in the AI era. Here's the thing: saying we're positioned to win is easy. Showing you is what today is all about. That brings me to our theme for the day, AI Made Real. Good morning, everyone. good morning everyone Thank you for joining us today. thank you for joining us today I'm Mike Rowshandel, Head of Investor Relations. i'm mike rowshandel head of investor relations Whether you're joining us live here in Boston or dialed in through the webcast, we appreciate you joining us today. whether you're joining us live here in boston or dialed in through the webcast we appreciate you joining us today We've been planning and preparing for this day for quite some time now, and I can tell you the energy in the backstage is buzzing. we've been planning and preparing for this day for quite some time now and i can tell you the energy in the backstage is buzzing Our entire leadership team is here, eager to take you inside our story, what we've built over the past three decades, and more importantly, the how and why we're positioned to be successful in the AI era. our entire leadership team is here eager to take you inside our story what we've built over the past three decades and more importantly the how and why we're positioned to be successful in the ai era Here's the thing: saying we're positioned to win is easy. here's the thing saying we're positioned to win is easy Showing you is what today is all about. showing you is what today is all about That brings me to our theme for the day, AI Made Real. that brings me to our theme for the day ai made real Through today's presentations, you'll hear real client testimonials, providing a deep sense of the unique value we continue to deliver each and every day. Before we begin, I would like to remind that today's presentation contains forward-looking statements which are subject to risk and uncertainties. Please refer to the safe harbor statement in our presentation materials and SEC filings for a discussion of factors that could cause actual results to differ. We'll also reference certain non-GAAP financial measures. Reconciliations to the most comparable GAAP measures can be found in the appendix of today's presentation. Now let me walk you through what to expect over the next few hours. First, some context. Our last major update was nearly four years ago, and to say a lot has changed would be an understatement. Through today's presentations, you'll hear real client testimonials, providing a deep sense of the unique value we continue to deliver each and every day. through today's presentations you'll hear real client testimonials providing a deep sense of the unique value we continue to deliver each and every day Before we begin, I would like to remind that today's presentation contains forward-looking statements which are subject to risk and uncertainties. before we begin i would like to remind that today's presentation contains forward-looking statements which are subject to risk and uncertainties Please refer to the safe harbor statement in our presentation materials and SEC filings for a discussion of factors that could cause actual results to differ. please refer to the safe harbor statement in our presentation materials and sec filings for a discussion of factors that could cause actual results to differ We'll also reference certain non-GAAP financial measures. we'll also reference certain non-gaap financial measures Reconciliations to the most comparable GAAP measures can be found in the appendix of today's presentation. reconciliations to the most comparable gaap measures can be found in the appendix of today's presentation Now let me walk you through what to expect over the next few hours. now let me walk you through what to expect over the next few hours First, some context. first some context Our last major update was nearly four years ago, and to say a lot has changed would be an understatement. our last major update was nearly four years ago and to say a lot has changed would be an understatement The macro, geopolitics, competitive dynamics, AI disruption, the evolution of IT services, and EPAM itself all look very different than back then. That's why a key objective of today's presentation is to provide important clarity on where we are today and where we're headed over the next few years. Let me quickly walk you through the agenda. The day is organized into two parts. In the first section, we'll provide an important update on our strategy, how we're transforming our go-to-market motions, and then we'll dive into a key AI section where we'll talk about AI native engineering and AI native business transformation. In the second section, we'll focus on our engineering DNA, our AI talent, global delivery engine, and then we'll have an engaging panel discussion with several of our geographic leaders. We'll then dive into our financial imperatives and then finally close with a Q&A session. The macro, geopolitics, competitive dynamics, AI disruption, the evolution of IT services, and EPAM itself all look very different than back then. the macro geopolitics competitive dynamics ai disruption the evolution of it services and epam itself all look very different than back then That's why a key objective of today's presentation is to provide important clarity on where we are today and where we're headed over the next few years. that's why a key objective of today's presentation is to provide important clarity on where we are today and where we're headed over the next few years Let me quickly walk you through the agenda. let me quickly walk you through the agenda The day is organized into two parts. the day is organized into two parts In the first section, we'll provide an important update on our strategy, how we're transforming our go-to-market motions, and then we'll dive into a key AI section where we'll talk about AI native engineering and AI native business transformation. in the first section we'll provide an important update on our strategy how we're transforming our go-to-market motions and then we'll dive into a key ai section where we'll talk about ai native engineering and ai native business transformation In the second section, we'll focus on our engineering DNA, our AI talent, global delivery engine, and then we'll have an engaging panel discussion with several of our geographic leaders. in the second section we'll focus on our engineering dna our ai talent global delivery engine and then we'll have an engaging panel discussion with several of our geographic leaders We'll then dive into our financial imperatives and then finally close with a Q&A session. we'll then dive into our financial imperatives and then finally close with a q&a session Finally, for those that have joined us live here in Boston, we invite you to please stick around after our main presentation. There's a highly interactive hour of client-led demonstrations and industry-led tours. These client demos and tours should give you a real sense of the AI capabilities we're delivering today. With that said, let's get kicked off with a quick video. With that, I would like to warmly welcome our Chief Executive Officer and President, Balazs Fejes, or better known as FB. Thank you. Finally, for those that have joined us live here in Boston, we invite you to please stick around after our main presentation. finally for those that have joined us live here in boston we invite you to please stick around after our main presentation There's a highly interactive hour of client-led demonstrations and industry-led tours. there's a highly interactive hour of client-led demonstrations and industry-led tours These client demos and tours should give you a real sense of the AI capabilities we're delivering today. these client demos and tours should give you a real sense of the ai capabilities we're delivering today With that said, let's get kicked off with a quick video. with that said let's get kicked off with a quick video With that, I would like to warmly welcome our Chief Executive Officer and President, Balazs Fejes, or better known as FB. with that i would like to warmly welcome our chief executive officer and president balazs fejes or better known as fb Thank you. thank you

Speaker 6: Mike, thank you very much. Good morning, good afternoon, good evening, everybody. Thanks for joining us here in Boston at our 2026 Investor and Analyst Day. My name is Balazs Fejes, just please call me FB. I'm not going to force you to learn how to pronounce Hungarian names. Mike probably spent two hours practicing how to pronounce it. You don't have to go through that. In the next probably 20 minutes, I would like to give you a strategic overview of EPAM, the market itself, how we are positioning ourselves to win in the AI native era. The first most important thing for me is that you have four things to take away from here. We are reinventing ourselves as a global leader in the AI transformation services space. Mike, thank you very much. mike thank you very much Good morning, good afternoon, good evening, everybody. good morning good afternoon good evening everybody Thanks for joining us here in Boston at our 2026 Investor and Analyst Day. thanks for joining us here in boston at our 2026 investor and analyst day My name is Balazs Fejes, just please call me FB. my name is balazs fejes just please call me fb I'm not going to force you to learn how to pronounce Hungarian names. i'm not going to force you to learn how to pronounce hungarian names Mike probably spent two hours practicing how to pronounce it. mike probably spent two hours practicing how to pronounce it You don't have to go through that. you don't have to go through that In the next probably 20 minutes, I would like to give you a strategic overview of EPAM, the market itself, how we are positioning ourselves to win in the AI native era. in the next probably 20 minutes i would like to give you a strategic overview of epam the market itself how we are positioning ourselves to win in the ai native era The first most important thing for me is that you have four things to take away from here. the first most important thing for me is that you have four things to take away from here We are reinventing ourselves as a global leader in the AI transformation services space. we are reinventing ourselves as a global leader in the ai transformation services space We are leveraging industry's best engineering talent in the industry so as to solve our clients' hardest, most complex business and technology problems. We are strengthening our internal and client-facing AI capabilities to capitalize on the global AI transformation, and we are executing a clear strategy to drive our next phase of profitable growth. Before we start, I think we need to really address the elephant in the room. We are reading the same headlines, same Substacks. I think watching the same Instagram, TikTok, YouTube Shorts, or YouTube videos. Even just today there are some new news popping out from everywhere. It tells a story. It tells a story that AI capabilities are growing really, really fast. This is true, but this is only one side of the story. We are leveraging industry's best engineering talent in the industry so as to solve our clients' hardest, most complex business and technology problems. we are leveraging industry's best engineering talent in the industry so as to solve our clients' hardest most complex business and technology problems We are strengthening our internal and client-facing AI capabilities to capitalize on the global AI transformation, and we are executing a clear strategy to drive our next phase of profitable growth. we are strengthening our internal and client-facing ai capabilities to capitalize on the global ai transformation and we are executing a clear strategy to drive our next phase of profitable growth Before we start, I think we need to really address the elephant in the room. before we start i think we need to really address the elephant in the room We are reading the same headlines, same Substacks. we are reading the same headlines same substacks I think watching the same Instagram, TikTok, YouTube Shorts, or YouTube videos. i think watching the same instagram tiktok youtube shorts or youtube videos Even just today there are some new news popping out from everywhere. even just today there are some new news popping out from everywhere It tells a story. it tells a story It tells a story that AI capabilities are growing really, really fast. it tells a story that ai capabilities are growing really really fast This is true, but this is only one side of the story. this is true but this is only one side of the story It only talks about AI capabilities growth, but it's not talking about the adoption rate in our societies and in our enterprise. These two are very different. Whereas AI capabilities are growing really fast, the adoption rate, the way people are changing how work gets done is growing much, much slower. There's a gap between those, and this gap is the opportunity for EPAM. EPAM is operating on the AI frontier. We transitioned into the AI frontier, and today we're going to show you how we've done that and how we're planning to stay there. How are we going to help our clients catch up to us using the learnings that we gained in the last three years? This is the opportunity of our lifetime. It only talks about AI capabilities growth, but it's not talking about the adoption rate in our societies and in our enterprise. it only talks about ai capabilities growth but it's not talking about the adoption rate in our societies and in our enterprise These two are very different. these two are very different Whereas AI capabilities are growing really fast, the adoption rate, the way people are changing how work gets done is growing much, much slower. whereas ai capabilities are growing really fast the adoption rate the way people are changing how work gets done is growing much much slower There's a gap between those, and this gap is the opportunity for EPAM. there's a gap between those and this gap is the opportunity for epam EPAM is operating on the AI frontier. epam is operating on the ai frontier We transitioned into the AI frontier, and today we're going to show you how we've done that and how we're planning to stay there. we transitioned into the ai frontier and today we're going to show you how we've done that and how we're planning to stay there How are we going to help our clients catch up to us using the learnings that we gained in the last three years? how are we going to help our clients catch up to us using the learnings that we gained in the last three years This is the opportunity of our lifetime. this is the opportunity of our lifetime Just a month ago, we were talking to most of you and updated you on our 2025 results, delivering almost a $5.456 billion revenue. This is our sixth consecutive quarterly revenue growth on reported basis, and we are really proud of it. We are delivering across 55 countries with 62,000 EPAMers with 56,000 delivery professionals. It took us 30 years to get here. We have been around, we've seen a lot. In 2025, we really delivered this growth across all the industries, across all the different geographies with a wide and very distributed presence. We don't have real concentration on this. We feel it's very important given the current economics and current situation. But let me remind you who we are. EPAM, we are a build and change organization. Just a month ago, we were talking to most of you and updated you on our 2025 results, delivering almost a $5.456 billion revenue. just a month ago we were talking to most of you and updated you on our 2025 results delivering almost a $5.456 billion revenue This is our sixth consecutive quarterly revenue growth on reported basis, and we are really proud of it. this is our sixth consecutive quarterly revenue growth on reported basis and we are really proud of it We are delivering across 55 countries with 62,000 EPAMers with 56,000 delivery professionals. we are delivering across 55 countries with 62,000 epamers with 56,000 delivery professionals It took us 30 years to get here. it took us 30 years to get here We have been around, we've seen a lot. we have been around we've seen a lot In 2025, we really delivered this growth across all the industries, across all the different geographies with a wide and very distributed presence. in 2025 we really delivered this growth across all the industries across all the different geographies with a wide and very distributed presence We don't have real concentration on this. we don't have real concentration on this We feel it's very important given the current economics and current situation. we feel it's very important given the current economics and current situation But let me remind you who we are. but let me remind you who we are EPAM, we are a build and change organization. epam we are a build and change organization In the last 30 years, that's what we've done. We honed our engineering heritage to actually build solutions for our clients. We are builders. We are delivering results relentlessly to our clients, helping them to navigate technology, geopolitical, and economic changes with our hybrid teams. That's who we are, and that's, I think, it's very important because we just entered the age of building. We are seeing that AI enables us to build new solutions, and that's our advantage, and that's our heritage. We are serving a diverse and global client list across 11 industries. 345 of our clients are part of Forbes Global 2000. 64 out of 100 are part of S&P 500 and the Global 2000 at the same time. The top 20 clients of ours on average had 13 years of tenure. In the last 30 years, that's what we've done. in the last 30 years that's what we've done We honed our engineering heritage to actually build solutions for our clients. we honed our engineering heritage to actually build solutions for our clients We are builders. we are builders We are delivering results relentlessly to our clients, helping them to navigate technology, geopolitical, and economic changes with our hybrid teams. we are delivering results relentlessly to our clients helping them to navigate technology geopolitical and economic changes with our hybrid teams That's who we are, and that's, I think, it's very important because we just entered the age of building. that's who we are and that's i think it's very important because we just entered the age of building We are seeing that AI enables us to build new solutions, and that's our advantage, and that's our heritage. we are seeing that ai enables us to build new solutions and that's our advantage and that's our heritage We are serving a diverse and global client list across 11 industries. 345 of our clients are part of Forbes Global 2000. 64 out of 100 are part of S&P 500 and the Global 2000 at the same time. we are serving a diverse and global client list across 11 industries 345 of our clients are part of forbes global 2000 64 out of 100 are part of s&p 500 and the global 2000 at the same time The top 20 clients of ours on average had 13 years of tenure. the top 20 clients of ours on average had 13 years of tenure We have deep relationships. 80+ of our top 100 clients are executing AI native projects with us. Actually, we're delivering for them new transformation projects. At the same time, we're winning new opportunities, we're winning new deals, and expanding our wallet share. We are positioned to harness the value of AI internally and also to capitalize on the growth opportunities, and I think that's very important as a key takeaway for us. Already in 2025, our results are benefited from AI. We delivered a very strong AI native and AI foundation momentum, which was built on five different foundations or pillars. We helped our client close the adoption gap with our skilled talent capabilities. We helped them optimize their delivery using AI SDLC, which we later on launched as part of AI/RUN. We have deep relationships. 80+ of our top 100 clients are executing AI native projects with us. we have deep relationships 80+ of our top 100 clients are executing ai native projects with us Actually, we're delivering for them new transformation projects. actually we're delivering for them new transformation projects At the same time, we're winning new opportunities, we're winning new deals, and expanding our wallet share. at the same time we're winning new opportunities we're winning new deals and expanding our wallet share We are positioned to harness the value of AI internally and also to capitalize on the growth opportunities, and I think that's very important as a key takeaway for us. we are positioned to harness the value of ai internally and also to capitalize on the growth opportunities and i think that's very important as a key takeaway for us Already in 2025, our results are benefited from AI. already in 2025 our results are benefited from ai We delivered a very strong AI native and AI foundation momentum, which was built on five different foundations or pillars. we delivered a very strong ai native and ai foundation momentum which was built on five different foundations or pillars We helped our client close the adoption gap with our skilled talent capabilities. we helped our client close the adoption gap with our skilled talent capabilities We helped them optimize their delivery using AI SDLC, which we later on launched as part of AI/RUN. we helped them optimize their delivery using ai sdlc which we later on launched as part of ai/run We helped them modernize their legacy system using AI, where we launched MFLens, which is a modernization toolkit. We also help our clients adopt physics AI and robotics. At the same time, we're helping clients globally to roll out sovereign AI, which is becoming more and more important in our increasingly more complex geopolitical space where we are operating in. TAM is very, very complex, and I'm sure all of you guys came here to understand how do we see TAM. Myself and not EPAM, we don't have a crystal ball. We just don't have that. We decided to borrow one from Gartner, I think. I'm going to use Gartner's crystal ball to try to explain to you where the market is going. We helped them modernize their legacy system using AI, where we launched MFLens, which is a modernization toolkit. we helped them modernize their legacy system using ai where we launched mflens which is a modernization toolkit We also help our clients adopt physics AI and robotics. we also help our clients adopt physics ai and robotics At the same time, we're helping clients globally to roll out sovereign AI, which is becoming more and more important in our increasingly more complex geopolitical space where we are operating in. at the same time we're helping clients globally to roll out sovereign ai which is becoming more and more important in our increasingly more complex geopolitical space where we are operating in TAM is very, very complex, and I'm sure all of you guys came here to understand how do we see TAM. tam is very very complex and i'm sure all of you guys came here to understand how do we see tam Myself and not EPAM, we don't have a crystal ball. myself and not epam we don't have a crystal ball We just don't have that. we just don't have that We decided to borrow one from Gartner, I think. we decided to borrow one from gartner i think I'm going to use Gartner's crystal ball to try to explain to you where the market is going. i'm going to use gartner's crystal ball to try to explain to you where the market is going Gartner predicts that the total market of IT services is going to grow to $1.8 trillion by 2029, which is a 5% CAGR. We are operating in a sub-segment, traditionally delivering solutions in business consulting, technology consulting, application implementation. This part of the segment is expected to go at 6.5% CAGR. It's a growing market and continues to grow. At the same time, we took another report, also from Gartner, which presented a very different picture. This really talks about the AI market itself. They are predicting that the total market of AI by 2029 will grow to $4.7 trillion. Gartner predicts that the total market of IT services is going to grow to $1.8 trillion by 2029, which is a 5% CAGR. gartner predicts that the total market of it services is going to grow to $1.8 trillion by 2029 which is a 5% cagr We are operating in a sub-segment, traditionally delivering solutions in business consulting, technology consulting, application implementation. we are operating in a sub-segment traditionally delivering solutions in business consulting technology consulting application implementation This part of the segment is expected to go at 6.5% CAGR. this part of the segment is expected to go at 6.5% cagr It's a growing market and continues to grow. At the same time, we took another report, also from Gartner, which presented a very different picture. it's a growing market and continues to grow. at the same time we took another report also from gartner which presented a very different picture This really talks about the AI market itself. this really talks about the ai market itself They are predicting that the total market of AI by 2029 will grow to $4.7 trillion. they are predicting that the total market of ai by 2029 will grow to $4.7 trillion That includes all the GPUs, all the data center investments people need to make in order to make it work, and the software and the AI services too. The AI services part, which we are really looking, is we comprise multiple sectors, and we actually took just one slice of it, what we call AI services plus AI cybersecurity. It's a very fast-growing sector. It's actually growing by double-digit CAGR, sometimes strong or very strong double-digit CAGR till 2029. Now, what's important to take away is that the or Gartner's definition, what's AI services, and our definition of AI native doesn't really match because they do include some parts, which is what we call AI-assisted revenue. But still, very important takeaway, it's a fast-growing segment of the market. That includes all the GPUs, all the data center investments people need to make in order to make it work, and the software and the AI services too. that includes all the gpus all the data center investments people need to make in order to make it work and the software and the ai services too The AI services part, which we are really looking, is we comprise multiple sectors, and we actually took just one slice of it, what we call AI services plus AI cybersecurity. the ai services part which we are really looking is we comprise multiple sectors and we actually took just one slice of it what we call ai services plus ai cybersecurity It's a very fast-growing sector. it's a very fast-growing sector It's actually growing by double-digit CAGR, sometimes strong or very strong double-digit CAGR till 2029. it's actually growing by double-digit cagr sometimes strong or very strong double-digit cagr till 2029 Now, what's important to take away is that the or Gartner's definition, what's AI services, and our definition of AI native doesn't really match because they do include some parts, which is what we call AI-assisted revenue. now what's important to take away is that the or gartner's definition what's ai services and our definition of ai native doesn't really match because they do include some parts which is what we call ai-assisted revenue But still, very important takeaway, it's a fast-growing segment of the market. but still very important takeaway it's a fast-growing segment of the market Now, I'm not going to be able to square off what's going to be replaced by AI or how much IT services is going to be impacted by itself, because nobody can, and we don't have the data for that. I'm just using this as information to demonstrate to you that it's a vast growing market which we're trying to tackle. On the other hand, I would like to really focus on why we are positioned ideally to win in this $1.3 trillion opportunity, which we call our AI services. EPAM has a client zero mentality. We spent three years building our capabilities, honing our capabilities, how to harness the power of AI on ourselves. This gives us credibility. Now, I'm not going to be able to square off what's going to be replaced by AI or how much IT services is going to be impacted by itself, because nobody can, and we don't have the data for that. now i'm not going to be able to square off what's going to be replaced by ai or how much it services is going to be impacted by itself because nobody can and we don't have the data for that I'm just using this as information to demonstrate to you that it's a vast growing market which we're trying to tackle. i'm just using this as information to demonstrate to you that it's a vast growing market which we're trying to tackle On the other hand, I would like to really focus on why we are positioned ideally to win in this $1.3 trillion opportunity, which we call our AI services. on the other hand i would like to really focus on why we are positioned ideally to win in this $1.3 trillion opportunity which we call our ai services EPAM has a client zero mentality. epam has a client zero mentality We spent three years building our capabilities, honing our capabilities, how to harness the power of AI on ourselves. we spent three years building our capabilities honing our capabilities how to harness the power of ai on ourselves This gives us credibility. this gives us credibility We have an engineering heritage, and in the age of building and actually applying AI, it's a very difficult thing to do, and you need real engineering power and you need engineering capabilities to make it really work. We understand how to manage talent, how to create the next generation talent, which is so important in the next couple of years. We have deep industry expertise because without in-industry expertise, you don't know what to automate, you don't know what to change and how to really take advantage of AI. The only thing you keep talking about is how to take cost out, and that has a limit. We have an engineering heritage, and in the age of building and actually applying AI, it's a very difficult thing to do, and you need real engineering power and you need engineering capabilities to make it really work. we have an engineering heritage and in the age of building and actually applying ai it's a very difficult thing to do and you need real engineering power and you need engineering capabilities to make it really work We understand how to manage talent, how to create the next generation talent, which is so important in the next couple of years. we understand how to manage talent how to create the next generation talent which is so important in the next couple of years We have deep industry expertise because without in-industry expertise, you don't know what to automate, you don't know what to change and how to really take advantage of AI. we have deep industry expertise because without in-industry expertise you don't know what to automate you don't know what to change and how to really take advantage of ai The only thing you keep talking about is how to take cost out, and that has a limit. the only thing you keep talking about is how to take cost out and that has a limit We have long-standing client relationships, clients who trust us, and you're going to see demonstrations of that to actually experiment with them, how to use and how to roll out AI using our expertise, what we gained in the last three years internally. We have an aspiration. Our aspiration is we wanna become the go-to partner for enterprises for AI transformation, which is built on 3 strategic pillars. Number 1, we wanna position and establish EPAM as a leading software engineering services provider. We wanna transform ourselves to be an AI native organization, and we want to launch new AI native offerings, which we're going to talk about. We have long-standing client relationships, clients who trust us, and you're going to see demonstrations of that to actually experiment with them, how to use and how to roll out AI using our expertise, what we gained in the last three years internally. we have long-standing client relationships clients who trust us and you're going to see demonstrations of that to actually experiment with them how to use and how to roll out ai using our expertise what we gained in the last three years internally We have an aspiration. we have an aspiration Our aspiration is we wanna become the go-to partner for enterprises for AI transformation, which is built on 3 strategic pillars. our aspiration is we wanna become the go-to partner for enterprises for ai transformation which is built on 3 strategic pillars Number 1, we wanna position and establish EPAM as a leading software engineering services provider. number 1 we wanna position and establish epam as a leading software engineering services provider We wanna transform ourselves to be an AI native organization, and we want to launch new AI native offerings, which we're going to talk about. we wanna transform ourselves to be an ai native organization and we want to launch new ai native offerings which we're going to talk about The key enablers to make this happen is talent skills, which we talked about, strategic partnership, extending strategic partnerships, which we just very recently entered a partnership with Cursor, which is a very important part of the puzzle, domain and vertical expertise, and continuous investments into internal products, internal IP. We have been accelerating our internal transformation. We are true to our values of being a client zero. We spent three years implementing and changing how to run our business, how to run recruitment, project staffing, talent management, how we can do management reporting and finance and legal using AI. We got some recognition due to that in best use of AI or the best competence and skills development using AI. We have been recognized for this effort. The key enablers to make this happen is talent skills, which we talked about, strategic partnership, extending strategic partnerships, which we just very recently entered a partnership with Cursor, which is a very important part of the puzzle, domain and vertical expertise, and continuous investments into internal products, internal IP. the key enablers to make this happen is talent skills which we talked about strategic partnership extending strategic partnerships which we just very recently entered a partnership with cursor which is a very important part of the puzzle domain and vertical expertise and continuous investments into internal products internal ip We have been accelerating our internal transformation. we have been accelerating our internal transformation We are true to our values of being a client zero. we are true to our values of being a client zero We spent three years implementing and changing how to run our business, how to run recruitment, project staffing, talent management, how we can do management reporting and finance and legal using AI. we spent three years implementing and changing how to run our business how to run recruitment project staffing talent management how we can do management reporting and finance and legal using ai We got some recognition due to that in best use of AI or the best competence and skills development using AI. we got some recognition due to that in best use of ai or the best competence and skills development using ai We have been recognized for this effort. we have been recognized for this effort Using all the knowledge what we gained in the last three years, back in autumn last year, we launched a codified go-to-market strategy under the brand name AI/RUN, which really addresses how to do AI native software engineering and how to do business transformation, which become an AI innovation-based business transformation. This consists of playbooks, blueprints, how to manage talent, and also tools, platforms behind it. This is based on real credible evidence, based on the three-year experiments which we're doing on ourselves. We're going to demonstrate it to you if you are in person in Boston with all the different shows around you. Also later today, we're going to actually show you how we implemented this tooling into our internal systems. We're creating new AI native business models and services. Using all the knowledge what we gained in the last three years, back in autumn last year, we launched a codified go-to-market strategy under the brand name AI/RUN, which really addresses how to do AI native software engineering and how to do business transformation, which become an AI innovation-based business transformation. using all the knowledge what we gained in the last three years back in autumn last year we launched a codified go-to-market strategy under the brand name ai/run which really addresses how to do ai native software engineering and how to do business transformation which become an ai innovation-based business transformation This consists of playbooks, blueprints, how to manage talent, and also tools, platforms behind it. this consists of playbooks blueprints how to manage talent and also tools platforms behind it This is based on real credible evidence, based on the three-year experiments which we're doing on ourselves. this is based on real credible evidence based on the three-year experiments which we're doing on ourselves We're going to demonstrate it to you if you are in person in Boston with all the different shows around you. we're going to demonstrate it to you if you are in person in boston with all the different shows around you Also later today, we're going to actually show you how we implemented this tooling into our internal systems. also later today we're going to actually show you how we implemented this tooling into our internal systems We're creating new AI native business models and services. we're creating new ai native business models and services These are net new services, net new revenue for EPAM. These services are agentic intelligent operations, AI native experiences. Just a couple of months ago, we launched Empathy Lab in North America, which is our AI native services, experiences launch, and brand name under this. AI native agentic operations and agentic factories and agentic security. We are doubling down on our growth drivers, talent, skills and capabilities. Extending on our 30 years of heritage, Sandra and Alexei will be updating you how we are creating the new talent, how we creating the new roadmap to actually create the new talent, and how we're sensing who has the capability to get there. We are verticalizing and actually deepening our industry experience. We are pushing our consultancy teams into our verticalized industries. These are net new services, net new revenue for EPAM. these are net new services net new revenue for epam These services are agentic intelligent operations, AI native experiences. these services are agentic intelligent operations ai native experiences Just a couple of months ago, we launched Empathy Lab in North America, which is our AI native services, experiences launch, and brand name under this. just a couple of months ago we launched empathy lab in north america which is our ai native services experiences launch and brand name under this AI native agentic operations and agentic factories and agentic security. ai native agentic operations and agentic factories and agentic security We are doubling down on our growth drivers, talent, skills and capabilities. we are doubling down on our growth drivers talent skills and capabilities Extending on our 30 years of heritage, Sandra and Alexei will be updating you how we are creating the new talent, how we creating the new roadmap to actually create the new talent, and how we're sensing who has the capability to get there. extending on our 30 years of heritage sandra and alexei will be updating you how we are creating the new talent how we creating the new roadmap to actually create the new talent and how we're sensing who has the capability to get there We are verticalizing and actually deepening our industry experience. we are verticalizing and actually deepening our industry experience We are pushing our consultancy teams into our verticalized industries. we are pushing our consultancy teams into our verticalized industries We're building, continue to build out internal platforms and IT assets, and of course, strategic partnerships where we need to strengthen, and we will double down our footprint. I think if you were following us in the last years, you heard a lot about our TelescopeAI. We invested decades in developing an enterprise backbone, digital backbone, which allowed us to manage our organization, manage us through crisis, manage us through different disruption, and continue allowing us to deliver with high quality. Now, we actually put an agentic backbone on top of it, which allows us, our teams and agents to interact with each other and actually take real-time data to drive better decision-making with higher quality output. Our leadership team has changed. We realigned our leadership structure around industries, brought in new members. You have the chance to interact with them throughout today. We're building, continue to build out internal platforms and IT assets, and of course, strategic partnerships where we need to strengthen, and we will double down our footprint. we're building continue to build out internal platforms and it assets and of course strategic partnerships where we need to strengthen and we will double down our footprint I think if you were following us in the last years, you heard a lot about our TelescopeAI. i think if you were following us in the last years you heard a lot about our telescopeai We invested decades in developing an enterprise backbone, digital backbone, which allowed us to manage our organization, manage us through crisis, manage us through different disruption, and continue allowing us to deliver with high quality. we invested decades in developing an enterprise backbone digital backbone which allowed us to manage our organization manage us through crisis manage us through different disruption and continue allowing us to deliver with high quality Now, we actually put an agentic backbone on top of it, which allows us, our teams and agents to interact with each other and actually take real-time data to drive better decision-making with higher quality output. Our leadership team has changed. now we actually put an agentic backbone on top of it which allows us our teams and agents to interact with each other and actually take real-time data to drive better decision-making with higher quality output. our leadership team has changed We realigned our leadership structure around industries, brought in new members. we realigned our leadership structure around industries brought in new members You have the chance to interact with them throughout today. you have the chance to interact with them throughout today Some of them is going to come on stage and present, but this is the team who is going to take us to the next level. Why invest in EPAM? We are the best positioned growth leader for enterprise AI transformation. Our AI native and foundational work is expanding, driving significant growth in markets. We are the strongest solution builders in the industry with proven track record of solving our clients' most complex problems. We have a clear strategy. We are focused on accelerating organic growth while driving margin expansion. Let's dive into the details. I would like to invite Elaina Shekhter, our Chief Strategy & Transformation Officer, on stage and to tell us how to transform our go-to-market. Thank you very much. Some of them is going to come on stage and present, but this is the team who is going to take us to the next level. some of them is going to come on stage and present but this is the team who is going to take us to the next level Why invest in EPAM? why invest in epam We are the best positioned growth leader for enterprise AI transformation. we are the best positioned growth leader for enterprise ai transformation Our AI native and foundational work is expanding, driving significant growth in markets. our ai native and foundational work is expanding driving significant growth in markets We are the strongest solution builders in the industry with proven track record of solving our clients' most complex problems. we are the strongest solution builders in the industry with proven track record of solving our clients' most complex problems We have a clear strategy. we have a clear strategy We are focused on accelerating organic growth while driving margin expansion. we are focused on accelerating organic growth while driving margin expansion Let's dive into the details. let's dive into the details I would like to invite Elaina Shekhter, our Chief Strategy & Transformation Officer, on stage and to tell us how to transform our go-to-market. i would like to invite elaina shekhter our chief strategy & transformation officer on stage and to tell us how to transform our go-to-market Thank you very much. thank you very much

Speaker 11: Thank you, FB. Good morning, everyone. I'm Elaina Shekhter, and as of two weeks ago, I'm the Chief Strategy and Transformation Officer. Before that, I was the Chief Marketing Officer, but today we have our brand-new Chief Marketing Officer here. Encourage everyone to meet Phil Walsh, who's gonna be walking around. Today, I wanna talk to you about what we're doing to transform our go-to-market approach. Over the years, EPAM has been particularly interested and really honestly obsessed with building the right kind of supply and addressing our customer needs in an overwhelming demand environment. Over the last few years, we've been investing significantly in our go-to-market approach and the transformation of all of our selling motions. Today, sorry for the clicker. Three key takeaways. We are transforming everything in the company. Thank you, FB. thank you fb Good morning, everyone. good morning everyone I'm Elaina Shekhter, and as of two weeks ago, I'm the Chief Strategy and Transformation Officer. i'm elaina shekhter and as of two weeks ago i'm the chief strategy and transformation officer Before that, I was the Chief Marketing Officer, but today we have our brand-new Chief Marketing Officer here. before that i was the chief marketing officer but today we have our brand-new chief marketing officer here Encourage everyone to meet Phil Walsh, who's gonna be walking around. encourage everyone to meet phil walsh who's gonna be walking around Today, I wanna talk to you about what we're doing to transform our go-to-market approach. today i wanna talk to you about what we're doing to transform our go-to-market approach Over the years, EPAM has been particularly interested and really honestly obsessed with building the right kind of supply and addressing our customer needs in an overwhelming demand environment. over the years epam has been particularly interested and really honestly obsessed with building the right kind of supply and addressing our customer needs in an overwhelming demand environment Over the last few years, we've been investing significantly in our go-to-market approach and the transformation of all of our selling motions. over the last few years we've been investing significantly in our go-to-market approach and the transformation of all of our selling motions Today, sorry for the clicker. today sorry for the clicker Three key takeaways. three key takeaways We are transforming everything in the company. we are transforming everything in the company As FB just shared, our digital platforms, our talent ecosystem, how we think about delivery, everything is being built around an AI native blueprint. The same is true with our go-to-market approach. We are responding to an AI-centric environment with changing everything that we do in order to more effectively meet our customers where they are. That means that we're building domain and vertical expertise into every motion. Every sales engagement, every capability is driven around deep knowledge of our customers and their domains. We're adapting the way we go to market through our programs that address customer reach to our engagement and commercial models, and we're doing it in sync with, or sometimes ahead of, emerging industry trends. EPAM predominantly serves the enterprise. As FB just shared, our digital platforms, our talent ecosystem, how we think about delivery, everything is being built around an AI native blueprint. as fb just shared our digital platforms our talent ecosystem how we think about delivery everything is being built around an ai native blueprint The same is true with our go-to-market approach. the same is true with our go-to-market approach We are responding to an AI-centric environment with changing everything that we do in order to more effectively meet our customers where they are. we are responding to an ai-centric environment with changing everything that we do in order to more effectively meet our customers where they are That means that we're building domain and vertical expertise into every motion. that means that we're building domain and vertical expertise into every motion Every sales engagement, every capability is driven around deep knowledge of our customers and their domains. every sales engagement every capability is driven around deep knowledge of our customers and their domains We're adapting the way we go to market through our programs that address customer reach to our engagement and commercial models, and we're doing it in sync with, or sometimes ahead of, emerging industry trends. we're adapting the way we go to market through our programs that address customer reach to our engagement and commercial models and we're doing it in sync with or sometimes ahead of emerging industry trends EPAM predominantly serves the enterprise. epam predominantly serves the enterprise We've been doing so for years, and although we have a significant footprint in ISVs and helping high tech and software companies build, they themselves are large enterprises. Our primary segment today are large companies, and their service needs, and their landscape of service needs has changed significantly with the rise of AI, and it has never been more complex. We've been doing so for years, and although we have a significant footprint in ISVs and helping high tech and software companies build, they themselves are large enterprises. we've been doing so for years and although we have a significant footprint in isvs and helping high tech and software companies build they themselves are large enterprises Our primary segment today are large companies, and their service needs, and their landscape of service needs has changed significantly with the rise of AI, and it has never been more complex. our primary segment today are large companies and their service needs and their landscape of service needs has changed significantly with the rise of ai and it has never been more complex Between market conditions that demand the addressing new competition, rising customer expectations, and all of the AI hype, all the technology trends which are constantly shifting on a daily basis, and our demand to meet expectations for advancing the transformations with AI, and the demands of the enterprises themselves, which are shifting also on a daily basis, demanding more strategy, more growth, better optimization programs, and overall better performance, and of course, a better use of capital, we are operating in a more complex enterprise environment than ever before. The market demands more flexibility, more capability, and more results delivered more relentlessly than ever before. To address these changing conditions, we are elevating our entire game and our go-to-market strategy with three key motions. Number one, we're shifting and extending our focus from building geographic capability to building full-scale capabilities. Between market conditions that demand the addressing new competition, rising customer expectations, and all of the AI hype, all the technology trends which are constantly shifting on a daily basis, and our demand to meet expectations for advancing the transformations with AI, and the demands of the enterprises themselves, which are shifting also on a daily basis, demanding more strategy, more growth, better optimization programs, and overall better performance, and of course, a better use of capital, we are operating in a more complex enterprise environment than ever before. between market conditions that demand the addressing new competition rising customer expectations and all of the ai hype all the technology trends which are constantly shifting on a daily basis and our demand to meet expectations for advancing the transformations with ai and the demands of the enterprises themselves which are shifting also on a daily basis demanding more strategy more growth better optimization programs and overall better performance and of course a better use of capital we are operating in a more complex enterprise environment than ever before The market demands more flexibility, more capability, and more results delivered more relentlessly than ever before. the market demands more flexibility more capability and more results delivered more relentlessly than ever before To address these changing conditions, we are elevating our entire game and our go-to-market strategy with three key motions. to address these changing conditions we are elevating our entire game and our go-to-market strategy with three key motions Number one, we're shifting and extending our focus from building geographic capability to building full-scale capabilities. number one we're shifting and extending our focus from building geographic capability to building full-scale capabilities Think about a full stack of capabilities that includes domain, vertical, and effectively forward deploying those capabilities to our client engagements. Secondly, we're integrating a consultative approach around the whole of the go-to-market strategy. No more is it consulting over here, engineering over there. Our goal with our go-to-market transformation is to bridge strategy and execution, and in doing so, create a consulting moat in addition to the engineering moat, which my colleagues will be talking about right after this. We're accelerating our motions, starting with partnerships, but not only. We are changing the way we address the market in total, direct-to-client motions, sales and marketing transformation, and of course, the work that we do continuously with our partners. Think about a full stack of capabilities that includes domain, vertical, and effectively forward deploying those capabilities to our client engagements. think about a full stack of capabilities that includes domain vertical and effectively forward deploying those capabilities to our client engagements Secondly, we're integrating a consultative approach around the whole of the go-to-market strategy. secondly we're integrating a consultative approach around the whole of the go-to-market strategy No more is it consulting over here, engineering over there. no more is it consulting over here engineering over there Our goal with our go-to-market transformation is to bridge strategy and execution, and in doing so, create a consulting moat in addition to the engineering moat, which my colleagues will be talking about right after this. our goal with our go-to-market transformation is to bridge strategy and execution and in doing so create a consulting moat in addition to the engineering moat which my colleagues will be talking about right after this We're accelerating our motions, starting with partnerships, but not only. we're accelerating our motions starting with partnerships but not only We are changing the way we address the market in total, direct-to-client motions, sales and marketing transformation, and of course, the work that we do continuously with our partners. we are changing the way we address the market in total direct-to-client motions sales and marketing transformation and of course the work that we do continuously with our partners What this means for us is that we are future-proofing an organization by creating a forward momentum that's bringing capabilities to clients to meet them where they are today. Our evolving focus areas are necessarily about value creation. At the mention of our hybrid teams, we have a long-standing history of building hybrid engineering teams. Today, our job for our customers is to build high-velocity performance teams that include consultants and engineers. We are prioritizing developing critical industry-specific skills. This could be vertical. This could be horizontal. We're doing that not only around AI, we're doing it with AI. More on this to come. What this means for us is that we are future-proofing an organization by creating a forward momentum that's bringing capabilities to clients to meet them where they are today. what this means for us is that we are future-proofing an organization by creating a forward momentum that's bringing capabilities to clients to meet them where they are today Our evolving focus areas are necessarily about value creation. our evolving focus areas are necessarily about value creation At the mention of our hybrid teams, we have a long-standing history of building hybrid engineering teams. at the mention of our hybrid teams we have a long-standing history of building hybrid engineering teams Today, our job for our customers is to build high-velocity performance teams that include consultants and engineers. today our job for our customers is to build high-velocity performance teams that include consultants and engineers We are prioritizing developing critical industry-specific skills. we are prioritizing developing critical industry-specific skills This could be vertical. this could be vertical This could be horizontal. this could be horizontal We're doing that not only around AI, we're doing it with AI. we're doing that not only around ai we're doing it with ai More on this to come. more on this to come Finally, we're creating a global delivery value creation network that's optimized not just across locations, and Larry will talk more about that, but also around specific services and skills and capabilities of individual people and high-performing teams. Part of this integration is not only to build consulting into everything that we do, but it's actually to open EPAM up to alternative and additional buyers in order to capture new market share. Earlier this year, we announced the expansion of Empathy Lab into North America, having had a very successful launch last year in Europe. Empathy is our AI native agency, and it offers choice to CMOs who increasingly have their own budgets for technology, and yes, also AI, to engage with an EPAM that is ready to meet them where they are in driving key transformation programs in a way that is not encumbered by traditional agency dynamics. Finally, we're creating a global delivery value creation network that's optimized not just across locations, and Larry will talk more about that, but also around specific services and skills and capabilities of individual people and high-performing teams. Part of this integration is not only to build consulting into everything that we do, but it's actually to open EPAM up to alternative and additional buyers in order to capture new market share. finally we're creating a global delivery value creation network that's optimized not just across locations and larry will talk more about that but also around specific services and skills and capabilities of individual people and high-performing teams. part of this integration is not only to build consulting into everything that we do but it's actually to open epam up to alternative and additional buyers in order to capture new market share Earlier this year, we announced the expansion of Empathy Lab into North America, having had a very successful launch last year in Europe. earlier this year we announced the expansion of empathy lab into north america having had a very successful launch last year in europe Empathy is our AI native agency, and it offers choice to CMOs who increasingly have their own budgets for technology, and yes, also AI, to engage with an EPAM that is ready to meet them where they are in driving key transformation programs in a way that is not encumbered by traditional agency dynamics. empathy is our ai native agency and it offers choice to cmos who increasingly have their own budgets for technology and yes also ai to engage with an epam that is ready to meet them where they are in driving key transformation programs in a way that is not encumbered by traditional agency dynamics We also continue to invest and integrate a EPAM Continuum, which is our consulting brand, and the changes there are material. We are upgrading the entire consultancy workflow with and around AI. In doing so, we're expanding our addressable market, and we believe not only are we serving our existing clients better, but we're expanding our opportunities to attract and build new client relationships. EPAM has always been known as a technology solutions expert. This is everything we've been doing for the past 30 years. Across all three brands and across all of our front doors, we're adopting and adapting our solutions proposition around AI. By integrating consulting, what we can deliver is end-to-end enterprise-grade scaled solutions in the absolute most complex environments. We also continue to invest and integrate a EPAM Continuum, which is our consulting brand, and the changes there are material. we also continue to invest and integrate a epam continuum which is our consulting brand and the changes there are material We are upgrading the entire consultancy workflow with and around AI. we are upgrading the entire consultancy workflow with and around ai In doing so, we're expanding our addressable market, and we believe not only are we serving our existing clients better, but we're expanding our opportunities to attract and build new client relationships. in doing so we're expanding our addressable market and we believe not only are we serving our existing clients better but we're expanding our opportunities to attract and build new client relationships EPAM has always been known as a technology solutions expert. epam has always been known as a technology solutions expert This is everything we've been doing for the past 30 years. this is everything we've been doing for the past 30 years Across all three brands and across all of our front doors, we're adopting and adapting our solutions proposition around AI. across all three brands and across all of our front doors we're adopting and adapting our solutions proposition around ai By integrating consulting, what we can deliver is end-to-end enterprise-grade scaled solutions in the absolute most complex environments. by integrating consulting what we can deliver is end-to-end enterprise-grade scaled solutions in the absolute most complex environments For those of you who are staying with us for the afternoon, as you walk around the space, you'll see just how complex complexity is. We're driving consulting to be in lockstep with technology, and in doing so, we can guide our clients on where and how AI should be used. We're helping to determine not only the right technology platforms, but the right operating models. We're identifying critical constraints and blockers around compliance, governance, security, very material, especially these days. We're actually starting to run AI native work streams and business models end to end. This is part of our engagement model transformation. We believe we are the absolute best partner to scale solutions around AI and build for the future in the most complex enterprise environments. What about how we sell? For those of you who are staying with us for the afternoon, as you walk around the space, you'll see just how complex complexity is. for those of you who are staying with us for the afternoon as you walk around the space you'll see just how complex complexity is We're driving consulting to be in lockstep with technology, and in doing so, we can guide our clients on where and how AI should be used. we're driving consulting to be in lockstep with technology and in doing so we can guide our clients on where and how ai should be used We're helping to determine not only the right technology platforms, but the right operating models. we're helping to determine not only the right technology platforms but the right operating models We're identifying critical constraints and blockers around compliance, governance, security, very material, especially these days. we're identifying critical constraints and blockers around compliance governance security very material especially these days We're actually starting to run AI native work streams and business models end to end. we're actually starting to run ai native work streams and business models end to end This is part of our engagement model transformation. this is part of our engagement model transformation We believe we are the absolute best partner to scale solutions around AI and build for the future in the most complex enterprise environments. we believe we are the absolute best partner to scale solutions around ai and build for the future in the most complex enterprise environments What about how we sell? what about how we sell To reach as many clients as possible with the most relevant propositions, we are transforming our full stack of sales and marketing motions in 2026. Everything that we've been doing for the last several years has been quote unquote digital. We were focused exclusively on driving optimization, modernization, and AI foundational work streams, and this continues today. In 2026, our value proposition includes the full digitization mix, but it is also driving optimization and agentic operations into both the growth agenda and the optimization agenda of our enterprise clients. How we manage sales is changing from account relationship management focus to really creating a hybrid seller, someone who is a forward deployed relationship manager who is at once a consultant, an engineer, and a relationship manager. We are adapting our pricing models. To reach as many clients as possible with the most relevant propositions, we are transforming our full stack of sales and marketing motions in 2026. to reach as many clients as possible with the most relevant propositions we are transforming our full stack of sales and marketing motions in 2026 Everything that we've been doing for the last several years has been quote unquote digital. everything that we've been doing for the last several years has been quote unquote digital We were focused exclusively on driving optimization, modernization, and AI foundational work streams, and this continues today. we were focused exclusively on driving optimization modernization and ai foundational work streams and this continues today In 2026, our value proposition includes the full digitization mix, but it is also driving optimization and agentic operations into both the growth agenda and the optimization agenda of our enterprise clients. in 2026 our value proposition includes the full digitization mix but it is also driving optimization and agentic operations into both the growth agenda and the optimization agenda of our enterprise clients How we manage sales is changing from account relationship management focus to really creating a hybrid seller, someone who is a forward deployed relationship manager who is at once a consultant, an engineer, and a relationship manager. how we manage sales is changing from account relationship management focus to really creating a hybrid seller someone who is a forward deployed relationship manager who is at once a consultant an engineer and a relationship manager We are adapting our pricing models. we are adapting our pricing models Of course, much of our business continues to be very much focused around T&M as much of the foundational work we continue to do is built around high-performance teams. But we're adding output-based, ROI-based, and business outcome-based models to our engagement mix successfully. Our sales cycle is changing from a more linear, sort of traditional sales cycle to one that is continuous. This is definitely a work in progress, and it will continue to evolve very quickly as we introduce agentic motions into both the top and the middle and the bottom of the funnel. Finally, marketing is transforming, and I'm very happy about that. From sequential brand through funnel activities, we are introducing a performance optimized marketing motion. With Phil on board, we're gonna be sharing a lot more with you on what that looks like. Of course, much of our business continues to be very much focused around T&M as much of the foundational work we continue to do is built around high-performance teams. of course much of our business continues to be very much focused around t&m as much of the foundational work we continue to do is built around high-performance teams But we're adding output-based, ROI-based, and business outcome-based models to our engagement mix successfully. but we're adding output-based roi-based and business outcome-based models to our engagement mix successfully Our sales cycle is changing from a more linear, sort of traditional sales cycle to one that is continuous. our sales cycle is changing from a more linear sort of traditional sales cycle to one that is continuous This is definitely a work in progress, and it will continue to evolve very quickly as we introduce agentic motions into both the top and the middle and the bottom of the funnel. this is definitely a work in progress and it will continue to evolve very quickly as we introduce agentic motions into both the top and the middle and the bottom of the funnel Finally, marketing is transforming, and I'm very happy about that. finally marketing is transforming and i'm very happy about that From sequential brand through funnel activities, we are introducing a performance optimized marketing motion. from sequential brand through funnel activities we are introducing a performance optimized marketing motion With Phil on board, we're gonna be sharing a lot more with you on what that looks like. with phil on board we're gonna be sharing a lot more with you on what that looks like Beyond investing, we are transforming our sales motions and our approach to market in order to capture additional market share. Nowhere is this more evident in the acceleration of our partnering motions. We've been making announcements over the last few months, and there will be many more to come, and quite quickly I might add. Today, our ecosystem of partners includes over 160 different partners. These include the platforms, AI native players, industry partners, universities, research labs, and such. This ecosystem is constantly being built out and adjusted to suit our solutions and consulting propositions. With our partners, our motion has changed from partner-centric channel motion to one that accelerates our propositions and our value to clients. Beyond investing, we are transforming our sales motions and our approach to market in order to capture additional market share. beyond investing we are transforming our sales motions and our approach to market in order to capture additional market share Nowhere is this more evident in the acceleration of our partnering motions. nowhere is this more evident in the acceleration of our partnering motions We've been making announcements over the last few months, and there will be many more to come, and quite quickly I might add. we've been making announcements over the last few months and there will be many more to come and quite quickly i might add Today, our ecosystem of partners includes over 160 different partners. today our ecosystem of partners includes over 160 different partners These include the platforms, AI native players, industry partners, universities, research labs, and such. these include the platforms ai native players industry partners universities research labs and such This ecosystem is constantly being built out and adjusted to suit our solutions and consulting propositions. this ecosystem is constantly being built out and adjusted to suit our solutions and consulting propositions With our partners, our motion has changed from partner-centric channel motion to one that accelerates our propositions and our value to clients. with our partners our motion has changed from partner-centric channel motion to one that accelerates our propositions and our value to clients We are elevating our market sensing capabilities and helping our partners do the same through very much tailored, dedicated, and often IP-based campaigns that we're bringing to market as we speak. We're also, in some cases, working with our partners to help them build their own platforms, and in doing so, driving delivery efficiency and effectiveness for their own build-out operations. These are some of the partners we work with today. FB mentioned Cursor. There's many more obviously, and there's now a number of very interesting ones that are coming up, particularly around the area of security. Over the last months, we've announced these are just really a subset of the things that we've announced, and so the point here is our relationships with our partners go way beyond credentials. We are elevating our market sensing capabilities and helping our partners do the same through very much tailored, dedicated, and often IP-based campaigns that we're bringing to market as we speak. we are elevating our market sensing capabilities and helping our partners do the same through very much tailored dedicated and often ip-based campaigns that we're bringing to market as we speak We're also, in some cases, working with our partners to help them build their own platforms, and in doing so, driving delivery efficiency and effectiveness for their own build-out operations. we're also in some cases working with our partners to help them build their own platforms and in doing so driving delivery efficiency and effectiveness for their own build-out operations These are some of the partners we work with today. these are some of the partners we work with today FB mentioned Cursor. fb mentioned cursor There's many more obviously, and there's now a number of very interesting ones that are coming up, particularly around the area of security. there's many more obviously and there's now a number of very interesting ones that are coming up particularly around the area of security Over the last months, we've announced these are just really a subset of the things that we've announced, and so the point here is our relationships with our partners go way beyond credentials. over the last months we've announced these are just really a subset of the things that we've announced and so the point here is our relationships with our partners go way beyond credentials We are pushing the edge of AI innovation, and we're doing that with our partners and with our clients. You're seeing us show up in market with AI wins, with being named the AI innovation partner for some of the largest CSPs, with announcing agents into multiple marketplaces. This work continues and will be built on as part of our evolving go-to-market strategy. I wanna leave you with three ideas. One, we are very serious about transforming our go-to-market approach. We understand that the environment has shifted into an AI-centric environment, and we are there for it. Number two, we believe domain and vertical expertise is a critical success factor, and it is creating not only an engineering moat for us, but also a consulting moat and positioning EPAM to win in an incredibly complex market. We are pushing the edge of AI innovation, and we're doing that with our partners and with our clients. we are pushing the edge of ai innovation and we're doing that with our partners and with our clients You're seeing us show up in market with AI wins, with being named the AI innovation partner for some of the largest CSPs, with announcing agents into multiple marketplaces. you're seeing us show up in market with ai wins with being named the ai innovation partner for some of the largest csps with announcing agents into multiple marketplaces This work continues and will be built on as part of our evolving go-to-market strategy. this work continues and will be built on as part of our evolving go-to-market strategy I wanna leave you with three ideas. i wanna leave you with three ideas One, we are very serious about transforming our go-to-market approach. one we are very serious about transforming our go-to-market approach We understand that the environment has shifted into an AI-centric environment, and we are there for it. we understand that the environment has shifted into an ai-centric environment and we are there for it Number two, we believe domain and vertical expertise is a critical success factor, and it is creating not only an engineering moat for us, but also a consulting moat and positioning EPAM to win in an incredibly complex market. number two we believe domain and vertical expertise is a critical success factor and it is creating not only an engineering moat for us but also a consulting moat and positioning epam to win in an incredibly complex market Finally, we are innovating and amplifying our partnership motions together with over 160 of the world's leading companies. We're using that to adapt our models, everything that we do, from how we deliver to how we engage with our clients. Of course, we're EPAM, so we're starting with the software development life cycle and the product development cycle. It gives me great pleasure to welcome my colleagues, Dmitry Tovpeko, who is our VP of AI Engineering, and Adam Auerbach, who's our VP and Head of AI Enablement, to the stage to tell you more. Thank you. Finally, we are innovating and amplifying our partnership motions together with over 160 of the world's leading companies. finally we are innovating and amplifying our partnership motions together with over 160 of the world's leading companies We're using that to adapt our models, everything that we do, from how we deliver to how we engage with our clients. we're using that to adapt our models everything that we do from how we deliver to how we engage with our clients Of course, we're EPAM, so we're starting with the software development life cycle and the product development cycle. of course we're epam so we're starting with the software development life cycle and the product development cycle It gives me great pleasure to welcome my colleagues, Dmitry Tovpeko, who is our VP of AI Engineering, and Adam Auerbach, who's our VP and Head of AI Enablement, to the stage to tell you more. it gives me great pleasure to welcome my colleagues dmitry tovpeko who is our vp of ai engineering and adam auerbach who's our vp and head of ai enablement to the stage to tell you more Thank you. thank you

Speaker 10: Good morning, everyone. My name is Dmitry Tovpeko. I lead AI engineering. Good morning, everyone. good morning everyone My name is Dmitry Tovpeko. my name is dmitry tovpeko I lead AI engineering. i lead ai engineering

Speaker 1: My name is Adam Auerbach. I'm head of AI enablement. My name is Adam Auerbach. my name is adam auerbach I'm head of AI enablement. i'm head of ai enablement

Speaker 10: Adam and I are gonna walk you through what is changing in how software gets built and why does it matter for EPAM business. Boris Cherny, the creator of Claude Code, one of the most advanced AI tools in the market, in the recent interview famously said that coding is largely solved with AI. If that's true, why do clients still need EPAM? We believe there are four reasons for that. First, enterprise complexity is growing, and the demand for complex engineering is infinite. Second, AI demands a new type of engineering discipline that is difficult to master, and engineering depth is our moat. Third, we are agentic platform builders, not just users or adopters. We are codifying delivery, and we are scaling a new type of engineering profile to run it. Adam and I are gonna walk you through what is changing in how software gets built and why does it matter for EPAM business. adam and i are gonna walk you through what is changing in how software gets built and why does it matter for epam business Boris Cherny, the creator of Claude Code, one of the most advanced AI tools in the market, in the recent interview famously said that coding is largely solved with AI. boris cherny the creator of claude code one of the most advanced ai tools in the market in the recent interview famously said that coding is largely solved with ai If that's true, why do clients still need EPAM? if that's true why do clients still need epam We believe there are four reasons for that. we believe there are four reasons for that First, enterprise complexity is growing, and the demand for complex engineering is infinite. first enterprise complexity is growing and the demand for complex engineering is infinite Second, AI demands a new type of engineering discipline that is difficult to master, and engineering depth is our moat. second ai demands a new type of engineering discipline that is difficult to master and engineering depth is our moat Third, we are agentic platform builders, not just users or adopters. third we are agentic platform builders not just users or adopters We are codifying delivery, and we are scaling a new type of engineering profile to run it. we are codifying delivery and we are scaling a new type of engineering profile to run it Fourth, what you build for clients today becomes the foundation for autonomous enterprise AI that they will require tomorrow, and every engagement brings us closer. Now let's talk about the first point, the first dimension, which is enterprise complexity. Our clients operate across eight simultaneous complexity dimensions, and each one of them get new requirements with AI. Strategy and economics. All of the client businesses are disrupted. They are discussing what they should be doing and how they should be transforming their primary core products. In addition to technology and product transformations they need to run internally. Data foundation. Your agents are as good as your data, and your enterprise data is not ready for AI. Vendor strategy is a good one. Fourth, what you build for clients today becomes the foundation for autonomous enterprise AI that they will require tomorrow, and every engagement brings us closer. fourth what you build for clients today becomes the foundation for autonomous enterprise ai that they will require tomorrow and every engagement brings us closer Now let's talk about the first point, the first dimension, which is enterprise complexity. now let's talk about the first point the first dimension which is enterprise complexity Our clients operate across eight simultaneous complexity dimensions, and each one of them get new requirements with AI. our clients operate across eight simultaneous complexity dimensions and each one of them get new requirements with ai Strategy and economics. strategy and economics All of the client businesses are disrupted. all of the client businesses are disrupted They are discussing what they should be doing and how they should be transforming their primary core products. they are discussing what they should be doing and how they should be transforming their primary core products In addition to technology and product transformations they need to run internally. in addition to technology and product transformations they need to run internally Data foundation. data foundation Your agents are as good as your data, and your enterprise data is not ready for AI. your agents are as good as your data and your enterprise data is not ready for ai Vendor strategy is a good one. vendor strategy is a good one Everybody's talking about which tools to select, but conversations also shifted to existing SaaS applications that are currently part of everybody's portfolio, and now clients are discussing whether they should retain them or they should rebuild these capabilities with AI. That creates a new set of questions and a new stream of engineering work. Every single dimension is getting new requirements. It is getting more and more complicated, and clients need a lot of help here. This is even before we talk about the changes that happens inside of software delivery and software engineering itself. Let's talk about it. When AI generates the code, the hard part becomes how do you create a system that generates it right. It all starts from design. Somebody needs to encode their specifications. What should go inside of them? Everybody's talking about which tools to select, but conversations also shifted to existing SaaS applications that are currently part of everybody's portfolio, and now clients are discussing whether they should retain them or they should rebuild these capabilities with AI. everybody's talking about which tools to select but conversations also shifted to existing saas applications that are currently part of everybody's portfolio and now clients are discussing whether they should retain them or they should rebuild these capabilities with ai That creates a new set of questions and a new stream of engineering work. that creates a new set of questions and a new stream of engineering work Every single dimension is getting new requirements. every single dimension is getting new requirements It is getting more and more complicated, and clients need a lot of help here. it is getting more and more complicated and clients need a lot of help here This is even before we talk about the changes that happens inside of software delivery and software engineering itself. this is even before we talk about the changes that happens inside of software delivery and software engineering itself Let's talk about it. let's talk about it When AI generates the code, the hard part becomes how do you create a system that generates it right. when ai generates the code the hard part becomes how do you create a system that generates it right It all starts from design. it all starts from design Somebody needs to encode their specifications. somebody needs to encode their specifications What should go inside of them? what should go inside of them All the domain knowledge, all the business workflows, all of these, proprietary knowledge in undocumented systems that is sitting inside of people's heads, all of that need to go there. Somebody need to architect the system. It is never a single agent that can do the work. This is always a complex agentic ecosystem that is ever-evolving and ever getting more and more complicated. Somebody needs to validate the output. Somebody need to judge. We see that the same tools produce very different results depending on engineers who are dealing with these tools, and the gap is getting wider. Finally, you need to connect these agentic ecosystems to your enterprise environments. With all of these established legacy ways of working, delivery pipelines, ecosystems, tools, integrations, all of that, and none of that was designed for AI, and now we need to deal with that. All the domain knowledge, all the business workflows, all of these, proprietary knowledge in undocumented systems that is sitting inside of people's heads, all of that need to go there. all the domain knowledge all the business workflows all of these proprietary knowledge in undocumented systems that is sitting inside of people's heads all of that need to go there Somebody need to architect the system. somebody need to architect the system It is never a single agent that can do the work. it is never a single agent that can do the work This is always a complex agentic ecosystem that is ever-evolving and ever getting more and more complicated. this is always a complex agentic ecosystem that is ever-evolving and ever getting more and more complicated Somebody needs to validate the output. somebody needs to validate the output Somebody need to judge. somebody need to judge We see that the same tools produce very different results depending on engineers who are dealing with these tools, and the gap is getting wider. we see that the same tools produce very different results depending on engineers who are dealing with these tools and the gap is getting wider Finally, you need to connect these agentic ecosystems to your enterprise environments. finally you need to connect these agentic ecosystems to your enterprise environments With all of these established legacy ways of working, delivery pipelines, ecosystems, tools, integrations, all of that, and none of that was designed for AI, and now we need to deal with that. with all of these established legacy ways of working delivery pipelines ecosystems tools integrations all of that and none of that was designed for ai and now we need to deal with that That creates a huge complexity inside of software engineering, which now is getting a new AI engineering discipline that didn't exist 12 months ago, to create AI engineering layer that can run the agents that are doing the work. This is exactly what we have done at EPAM. We codified the agentic system, the entire delivery pipeline with agents. I'm not talking about agents augmentation. That was easy part, so this is gone. What we are doing, we are creating a brand new, from the ground up, AI native ways of working that we codified in a repeatable pipeline, and that's the blueprint. Now, the blueprint is an easy part. The hard part is how you can actually scale it. That creates a huge complexity inside of software engineering, which now is getting a new AI engineering discipline that didn't exist 12 months ago, to create AI engineering layer that can run the agents that are doing the work. that creates a huge complexity inside of software engineering which now is getting a new ai engineering discipline that didn't exist 12 months ago to create ai engineering layer that can run the agents that are doing the work This is exactly what we have done at EPAM. this is exactly what we have done at epam We codified the agentic system, the entire delivery pipeline with agents. we codified the agentic system the entire delivery pipeline with agents I'm not talking about agents augmentation. i'm not talking about agents augmentation That was easy part, so this is gone. that was easy part so this is gone What we are doing, we are creating a brand new, from the ground up, AI native ways of working that we codified in a repeatable pipeline, and that's the blueprint. what we are doing we are creating a brand new from the ground up ai native ways of working that we codified in a repeatable pipeline and that's the blueprint Now, the blueprint is an easy part. now the blueprint is an easy part The hard part is how you can actually scale it. the hard part is how you can actually scale it In order to run it, you need a new type of engineer to deal with that. Traditional, narrow, specialized software engineers are actually not good in benefiting from these kind of blueprints. They can get maybe 10%, maybe 15%, but all of these stories about 2x, 3x, they require a very different profile. Somebody who can own engineering tasks end to end across all stages of SDLC, across multiple technology stacks, and this is where it is becoming very complicated. They need to be fluent in new AI tooling. They should be using them in very different ways. They should be able to judge whether the outputs at every step in the way are what they should be. This is what we call full stack agentic engineer profile, and scaling this profile is the hard part. In order to run it, you need a new type of engineer to deal with that. Traditional, narrow, specialized software engineers are actually not good in benefiting from these kind of blueprints. in order to run it you need a new type of engineer to deal with that. traditional narrow specialized software engineers are actually not good in benefiting from these kind of blueprints They can get maybe 10%, maybe 15%, but all of these stories about 2x, 3x, they require a very different profile. they can get maybe 10% maybe 15% but all of these stories about 2x 3x they require a very different profile Somebody who can own engineering tasks end to end across all stages of SDLC, across multiple technology stacks, and this is where it is becoming very complicated. somebody who can own engineering tasks end to end across all stages of sdlc across multiple technology stacks and this is where it is becoming very complicated They need to be fluent in new AI tooling. they need to be fluent in new ai tooling They should be using them in very different ways. they should be using them in very different ways They should be able to judge whether the outputs at every step in the way are what they should be. they should be able to judge whether the outputs at every step in the way are what they should be This is what we call full stack agentic engineer profile, and scaling this profile is the hard part. this is what we call full stack agentic engineer profile and scaling this profile is the hard part Alexei and Sandra later today are gonna talk in more details about it. The question is, can anyone do this? We believe there are two things that are required to operate this at scale, and most companies cannot assemble both. First, you've got to have strong engineering culture and depth. This is not an upskilling program. This is not a scaled certification exercise for particular skill set. You have to start from the very high point from the very beginning. You have to have that as a part of your DNA already in order to be able to run in this race. We set these high standards many years ago, and now, 30 more years later, we are starting from a much higher point than many. Second, you've got to have delivery volume. Alexei and Sandra later today are gonna talk in more details about it. alexei and sandra later today are gonna talk in more details about it The question is, can anyone do this? the question is can anyone do this We believe there are two things that are required to operate this at scale, and most companies cannot assemble both. we believe there are two things that are required to operate this at scale and most companies cannot assemble both First, you've got to have strong engineering culture and depth. first you've got to have strong engineering culture and depth This is not an upskilling program. this is not an upskilling program This is not a scaled certification exercise for particular skill set. this is not a scaled certification exercise for particular skill set You have to start from the very high point from the very beginning. you have to start from the very high point from the very beginning You have to have that as a part of your DNA already in order to be able to run in this race. you have to have that as a part of your dna already in order to be able to run in this race We set these high standards many years ago, and now, 30 more years later, we are starting from a much higher point than many. we set these high standards many years ago and now 30 more years later we are starting from a much higher point than many Second, you've got to have delivery volume. second you've got to have delivery volume You have to be able to run this pipeline against real enterprises over and over again, and this is where blueprint are getting battle tested. This is where they are becoming real. This is where you are facing real legacy problems. This is where they are becoming scalable, and they can bring value to our clients. Why we think most firms cannot assemble both? Of course, arbitrage firms, their model was optimized for narrow specialized engineer. Low rates, low complexity work, and they require particular profile to make it a profitable business, and we believe that these firms are exposed. EPAM hasn't been ever really playing a role there. We approach it differently. Strategy firms, they have intellectual depth, but they don't have muscle on the ground to make it real, to actually deliver on these promises. You have to be able to run this pipeline against real enterprises over and over again, and this is where blueprint are getting battle tested. you have to be able to run this pipeline against real enterprises over and over again and this is where blueprint are getting battle tested This is where they are becoming real. this is where they are becoming real This is where you are facing real legacy problems. this is where you are facing real legacy problems This is where they are becoming scalable, and they can bring value to our clients. this is where they are becoming scalable and they can bring value to our clients Why we think most firms cannot assemble both? why we think most firms cannot assemble both Of course, arbitrage firms, their model was optimized for narrow specialized engineer. of course arbitrage firms their model was optimized for narrow specialized engineer Low rates, low complexity work, and they require particular profile to make it a profitable business, and we believe that these firms are exposed. low rates low complexity work and they require particular profile to make it a profitable business and we believe that these firms are exposed EPAM hasn't been ever really playing a role there. epam hasn't been ever really playing a role there We approach it differently. we approach it differently Strategy firms, they have intellectual depth, but they don't have muscle on the ground to make it real, to actually deliver on these promises. strategy firms they have intellectual depth but they don't have muscle on the ground to make it real to actually deliver on these promises Product companies, they have engineering culture, they have great products, but they're only integrating with the enterprises. They're not working from within inside of this complexity. EPAM has both. We have the engineering culture, and we have the volume, and that's the mode. We believe that AI gets it wider. This only comes from doing the work. You are as good as your delivery. In AI, the right way to build reveals itself only through doing. No one figured it out from a whiteboard. All the great founders right now of AI tools, they're all hands-on. They all have a ton of experience. This is what we have built, and this is why we believe it is hard to replicate. Now Adam is going to walk you through how we are scaling this across our clients. Adam. Product companies, they have engineering culture, they have great products, but they're only integrating with the enterprises. product companies they have engineering culture they have great products but they're only integrating with the enterprises They're not working from within inside of this complexity. they're not working from within inside of this complexity EPAM has both. epam has both We have the engineering culture, and we have the volume, and that's the mode. we have the engineering culture and we have the volume and that's the mode We believe that AI gets it wider. we believe that ai gets it wider This only comes from doing the work. this only comes from doing the work You are as good as your delivery. you are as good as your delivery In AI, the right way to build reveals itself only through doing. in ai the right way to build reveals itself only through doing No one figured it out from a whiteboard. no one figured it out from a whiteboard All the great founders right now of AI tools, they're all hands-on. all the great founders right now of ai tools they're all hands-on They all have a ton of experience. they all have a ton of experience This is what we have built, and this is why we believe it is hard to replicate. this is what we have built and this is why we believe it is hard to replicate Now Adam is going to walk you through how we are scaling this across our clients. now adam is going to walk you through how we are scaling this across our clients Adam. adam

Speaker 1: Thank you, Dima. What Dima is describing to you is what we call level three maturity. What we have found is that there are multiple levels to this journey, and most people start at level one. Level one is they have access to Copilot, Cursor, a code assist tool, but no one really uses that tool. If you buy a tool, doesn't mean that people are going to use it. People need coaching. They need training. They need support. What they ultimately will find out is that that tool optimizes one aspect of development, coding. Yes, does it create efficiencies for developers? Sure. As Dima just said, there's much more to the software development life cycle than just writing code, and that's why you also need agents, and that's what level two is. Thank you, Dima. thank you dima What Dima is describing to you is what we call level three maturity. what dima is describing to you is what we call level three maturity What we have found is that there are multiple levels to this journey, and most people start at level one. what we have found is that there are multiple levels to this journey and most people start at level one Level one is they have access to Copilot, Cursor, a code assist tool, but no one really uses that tool. level one is they have access to copilot cursor a code assist tool but no one really uses that tool If you buy a tool, doesn't mean that people are going to use it. if you buy a tool doesn't mean that people are going to use it People need coaching. people need coaching They need training. they need training They need support. they need support What they ultimately will find out is that that tool optimizes one aspect of development, coding. what they ultimately will find out is that that tool optimizes one aspect of development coding Yes, does it create efficiencies for developers? yes does it create efficiencies for developers Sure. sure As Dima just said, there's much more to the software development life cycle than just writing code, and that's why you also need agents, and that's what level two is. as dima just said there's much more to the software development life cycle than just writing code and that's why you also need agents and that's what level two is Level two is this combination of a code assist tool with agents to help accelerate your current ways of working. That's the next challenge. Yes, level two will create the efficiencies that people are expecting with AI, faster cycle time, higher quality, better productivity. When Dima talks about delivery as code, he's really talking about a whole new way of working, where we get to what's called spec-driven development. That means your process has to change. I have been in IT for 25 years. I know I don't look that old. When I first started out, it was around moving from waterfall to agile. Companies are still struggling with that today. Now we're saying, "Hey, we're going to introduce this new way of working." We have to get over the fear and resistance from people. Level two is this combination of a code assist tool with agents to help accelerate your current ways of working. level two is this combination of a code assist tool with agents to help accelerate your current ways of working That's the next challenge. that's the next challenge Yes, level two will create the efficiencies that people are expecting with AI, faster cycle time, higher quality, better productivity. yes level two will create the efficiencies that people are expecting with ai faster cycle time higher quality better productivity When Dima talks about delivery as code, he's really talking about a whole new way of working, where we get to what's called spec-driven development. when dima talks about delivery as code he's really talking about a whole new way of working where we get to what's called spec-driven development That means your process has to change. that means your process has to change I have been in IT for 25 years. i have been in it for 25 years I know I don't look that old. i know i don't look that old When I first started out, it was around moving from waterfall to agile. when i first started out it was around moving from waterfall to agile Companies are still struggling with that today. companies are still struggling with that today Now we're saying, "Hey, we're going to introduce this new way of working." We have to get over the fear and resistance from people. now we're saying "hey we're going to introduce this new way of working." we have to get over the fear and resistance from people Once you get to some level of accomplishment, there's yet further improvement. This is a long journey that people are on to get all the way there. We do luckily have some really great case studies like PostNL, where we are delivering agents, we are getting them to this new world, this new reality, and that is, as Dima said, that moat is the fact that we have so many of these projects right now, and we're learning from ourselves and getting this experience that we can then bring to our clients, and that really sets us apart. As FB mentioned, we've created something called AI/RUN, and that's our suite of consulting services and education and tools around how to drive this transformation for our clients. We're focused here on engineering. Once you get to some level of accomplishment, there's yet further improvement. once you get to some level of accomplishment there's yet further improvement This is a long journey that people are on to get all the way there. this is a long journey that people are on to get all the way there We do luckily have some really great case studies like PostNL, where we are delivering agents, we are getting them to this new world, this new reality, and that is, as Dima said, that moat is the fact that we have so many of these projects right now, and we're learning from ourselves and getting this experience that we can then bring to our clients, and that really sets us apart. we do luckily have some really great case studies like postnl where we are delivering agents we are getting them to this new world this new reality and that is as dima said that moat is the fact that we have so many of these projects right now and we're learning from ourselves and getting this experience that we can then bring to our clients and that really sets us apart As FB mentioned, we've created something called AI/RUN, and that's our suite of consulting services and education and tools around how to drive this transformation for our clients. as fb mentioned we've created something called ai/run and that's our suite of consulting services and education and tools around how to drive this transformation for our clients We're focused here on engineering. we're focused here on engineering Nir and Eli, who are going to speak next, they're going to talk about how we're doing this for the business 'cause there's a lot of similarities here. I'm gonna double-click into each one of these for a second. The first one is blueprints. Dima, you talk to a lot of CIOs. How many IT leaders can really articulate the current levels of productivity for their organization? Nir and Eli, who are going to speak next, they're going to talk about how we're doing this for the business 'cause there's a lot of similarities here. nir and eli who are going to speak next they're going to talk about how we're doing this for the business 'cause there's a lot of similarities here I'm gonna double-click into each one of these for a second. i'm gonna double-click into each one of these for a second The first one is blueprints. the first one is blueprints Dima, you talk to a lot of CIOs. dima you talk to a lot of cios How many IT leaders can really articulate the current levels of productivity for their organization? how many it leaders can really articulate the current levels of productivity for their organization

Speaker 10: Well, not very many. Definitely not on the second meeting. Well, not very many. well not very many Definitely not on the second meeting. definitely not on the second meeting

Speaker 1: If the board is saying, "Hey, I wanna see 20% productivity boost from AI," that's a problem because they don't know what their productivity is today. For the last many years, I've been at EPAM for eight years now, we have something called Engineering Excellence. It's what makes EPAM so special, our engineering talent, how we really raise the bar in our delivery centers, in our projects, and we have a consulting offering that we've been running with our clients where we help them baseline their teams, their performance. We establish those KPIs and then build improvement plans so that they can be more agile and leverage DevOps and get to continuous delivery. If the board is saying, "Hey, I wanna see 20% productivity boost from AI," that's a problem because they don't know what their productivity is today. if the board is saying "hey i wanna see 20% productivity boost from ai," that's a problem because they don't know what their productivity is today For the last many years, I've been at EPAM for eight years now, we have something called Engineering Excellence. for the last many years i've been at epam for eight years now we have something called engineering excellence It's what makes EPAM so special, our engineering talent, how we really raise the bar in our delivery centers, in our projects, and we have a consulting offering that we've been running with our clients where we help them baseline their teams, their performance. it's what makes epam so special our engineering talent how we really raise the bar in our delivery centers in our projects and we have a consulting offering that we've been running with our clients where we help them baseline their teams their performance We establish those KPIs and then build improvement plans so that they can be more agile and leverage DevOps and get to continuous delivery. we establish those kpis and then build improvement plans so that they can be more agile and leverage devops and get to continuous delivery We're able to take that same methodology, go to an organization, understand how are they working, and then from that figure out, okay, where is the place that AI is gonna have the best value for you? Instead of just saying, "Hey, let me, you know, be haphazard," we can be really targeted in which agents we build, the education, and then we can track the progress. We win projects because we can really articulate, "This is how fast you're moving today. This is your current levels of quality, and then here's the benefit of of AI." We have a really great case study with Edward Jones. We're working with them right now. It started a year ago with a pilot. We're able to take that same methodology, go to an organization, understand how are they working, and then from that figure out, okay, where is the place that AI is gonna have the best value for you? we're able to take that same methodology go to an organization understand how are they working and then from that figure out okay where is the place that ai is gonna have the best value for you Instead of just saying, "Hey, let me, you know, be haphazard," we can be really targeted in which agents we build, the education, and then we can track the progress. instead of just saying "hey let me you know be haphazard," we can be really targeted in which agents we build the education and then we can track the progress We win projects because we can really articulate, "This is how fast you're moving today. we win projects because we can really articulate "this is how fast you're moving today This is your current levels of quality, and then here's the benefit of of AI." We have a really great case study with Edward Jones. this is your current levels of quality and then here's the benefit of of ai." we have a really great case study with edward jones We're working with them right now. we're working with them right now It started a year ago with a pilot. it started a year ago with a pilot We were able to show with our products and copilot the efficiency gains we could deliver in a short amount of time, and now we're in the process of scaling it out to the rest of the organization, and we have many of these projects happening right now. Dima showed you this picture, delivery as code, and I just wanted to go back to it for a little bit just to articulate a couple things. In the blue boxes, which maybe are a little tough to see, these represent different agents, or maybe it's agents calling agents. There's maybe 10 or so, maybe a little bit more, in this picture. If you're an organization, you can't just apply agents blindly to all of your teams. Every team supports a different application. We were able to show with our products and copilot the efficiency gains we could deliver in a short amount of time, and now we're in the process of scaling it out to the rest of the organization, and we have many of these projects happening right now. we were able to show with our products and copilot the efficiency gains we could deliver in a short amount of time and now we're in the process of scaling it out to the rest of the organization and we have many of these projects happening right now Dima showed you this picture, delivery as code, and I just wanted to go back to it for a little bit just to articulate a couple things. dima showed you this picture delivery as code and i just wanted to go back to it for a little bit just to articulate a couple things In the blue boxes, which maybe are a little tough to see, these represent different agents, or maybe it's agents calling agents. in the blue boxes which maybe are a little tough to see these represent different agents or maybe it's agents calling agents There's maybe 10 or so, maybe a little bit more, in this picture. there's maybe 10 or so maybe a little bit more in this picture If you're an organization, you can't just apply agents blindly to all of your teams. if you're an organization you can't just apply agents blindly to all of your teams Every team supports a different application. every team supports a different application A large enterprise could have thousands of applications that make up their platforms. What that means is that every team is going to need a different set of agents tuned for them. They have different tools, different technology stacks, different ways of working. The scale of this gets pretty big pretty quickly. What we have done is we have built a set of tools for ourselves under the AI/RUN platform umbrella. We have things like DIAL, CodeMie, ELITEA, Agentic QA, which we can bring to a client to accelerate their adoption. As well as we can handle how you can take an agent and basically copy and paste it and tune it quickly for the next set of teams and manage that at scale with the observability and governance that's required for a large enterprise. A large enterprise could have thousands of applications that make up their platforms. a large enterprise could have thousands of applications that make up their platforms What that means is that every team is going to need a different set of agents tuned for them. what that means is that every team is going to need a different set of agents tuned for them They have different tools, different technology stacks, different ways of working. they have different tools different technology stacks different ways of working The scale of this gets pretty big pretty quickly. the scale of this gets pretty big pretty quickly What we have done is we have built a set of tools for ourselves under the AI/RUN platform umbrella. what we have done is we have built a set of tools for ourselves under the ai/run platform umbrella We have things like DIAL, CodeMie, ELITEA, Agentic QA, which we can bring to a client to accelerate their adoption. we have things like dial codemie elitea agentic qa which we can bring to a client to accelerate their adoption As well as we can handle how you can take an agent and basically copy and paste it and tune it quickly for the next set of teams and manage that at scale with the observability and governance that's required for a large enterprise. as well as we can handle how you can take an agent and basically copy and paste it and tune it quickly for the next set of teams and manage that at scale with the observability and governance that's required for a large enterprise Shameless plug, we have a booth, so later on if you wanna see a demo of the tools, we can definitely show you. The tools are real, and they're spectacular. We built these tools a couple years ago. It was really important for us to be able to use them to learn and now, we definitely have projects where we don't use our tools, but what it allows us also to do is quickly understand what are those people and process limitations that are preventing wide scale adoption at a client quickly. We can bake this into our own projects. If a client's going through the transformation that takes, you know, many months, maybe years, we can come in with our tools quickly deployed with our full stack agentic engineers and really be able to deliver the value of AI quickly. Shameless plug, we have a booth, so later on if you wanna see a demo of the tools, we can definitely show you. shameless plug we have a booth so later on if you wanna see a demo of the tools we can definitely show you The tools are real, and they're spectacular. the tools are real and they're spectacular We built these tools a couple years ago. we built these tools a couple years ago It was really important for us to be able to use them to learn and now, we definitely have projects where we don't use our tools, but what it allows us also to do is quickly understand what are those people and process limitations that are preventing wide scale adoption at a client quickly. it was really important for us to be able to use them to learn and now we definitely have projects where we don't use our tools but what it allows us also to do is quickly understand what are those people and process limitations that are preventing wide scale adoption at a client quickly We can bake this into our own projects. we can bake this into our own projects If a client's going through the transformation that takes, you know, many months, maybe years, we can come in with our tools quickly deployed with our full stack agentic engineers and really be able to deliver the value of AI quickly. if a client's going through the transformation that takes you know many months maybe years we can come in with our tools quickly deployed with our full stack agentic engineers and really be able to deliver the value of ai quickly Then lastly, before I hand it back over to Dima, when you talk about level one, an agile team, people are working in silos. When they start to use AI, they can create some efficiencies for their tasks. In the industry, we've had this term called a T-shaped engineer, and a T-shaped engineer means that I have this one skill, maybe I'm a mobile developer, but then I can also maybe do some API development and maybe some backend work, right? That's T-shaped. With AI and agents, I can really deliver on this promise because that T-shaped person can be sometimes a unicorn. With AI, I can give people agents to really help expand what they're able to do. Then lastly, before I hand it back over to Dima, when you talk about level one, an agile team, people are working in silos. then lastly before i hand it back over to dima when you talk about level one an agile team people are working in silos When they start to use AI, they can create some efficiencies for their tasks. when they start to use ai they can create some efficiencies for their tasks In the industry, we've had this term called a T-shaped engineer, and a T-shaped engineer means that I have this one skill, maybe I'm a mobile developer, but then I can also maybe do some API development and maybe some backend work, right? in the industry we've had this term called a t-shaped engineer and a t-shaped engineer means that i have this one skill maybe i'm a mobile developer but then i can also maybe do some api development and maybe some backend work right That's T-shaped. that's t-shaped With AI and agents, I can really deliver on this promise because that T-shaped person can be sometimes a unicorn. with ai and agents i can really deliver on this promise because that t-shaped person can be sometimes a unicorn With AI, I can give people agents to really help expand what they're able to do. with ai i can give people agents to really help expand what they're able to do I could have a front-end developer who now is able to do, like Dima said, full-stack engineering. They can do work across all levels of the application, of the platform, and do many different things. Now with AI, they really can run the entire software factory, that delivery as code. Now what we see in our new teams is this combination of this full-stack agentic engineer with combination of product and design, and this is how we deliver products in this AI-native world. Dima, I think you're gonna talk to us about why, while this might shrink some of our teams, the demand is actually far bigger. I could have a front-end developer who now is able to do, like Dima said, full-stack engineering. i could have a front-end developer who now is able to do like dima said full-stack engineering They can do work across all levels of the application, of the platform, and do many different things. they can do work across all levels of the application of the platform and do many different things Now with AI, they really can run the entire software factory, that delivery as code. now with ai they really can run the entire software factory that delivery as code Now what we see in our new teams is this combination of this full-stack agentic engineer with combination of product and design, and this is how we deliver products in this AI-native world. now what we see in our new teams is this combination of this full-stack agentic engineer with combination of product and design and this is how we deliver products in this ai-native world Dima, I think you're gonna talk to us about why, while this might shrink some of our teams, the demand is actually far bigger. dima i think you're gonna talk to us about why while this might shrink some of our teams the demand is actually far bigger

Speaker 10: Yeah. Thanks, Adam. Now I'm also eager to look at the tools again. Adam just took you under the hood. Now let's talk about the implications to the market. The common assumption is the faster we can go, the fewer engineers you need. For a lot of work that's true. We definitely see this on the ground. At the same time, this is actually not the case in many places where we operate with our clients. There is a fixed pile of work at the top. Maintenance, application support, second-tier applications development. There is only so much work that you can do, and this pile of work is doomed to be shrinking over and over. All the firms that operate in there, they're all exposed. As I said previously, this has not been the place where EPAM was generally operating. Yeah. yeah Thanks, Adam. thanks adam Now I'm also eager to look at the tools again. now i'm also eager to look at the tools again Adam just took you under the hood. adam just took you under the hood Now let's talk about the implications to the market. now let's talk about the implications to the market The common assumption is the faster we can go, the fewer engineers you need. the common assumption is the faster we can go the fewer engineers you need For a lot of work that's true. for a lot of work that's true We definitely see this on the ground. we definitely see this on the ground At the same time, this is actually not the case in many places where we operate with our clients. at the same time this is actually not the case in many places where we operate with our clients There is a fixed pile of work at the top. there is a fixed pile of work at the top Maintenance, application support, second-tier applications development. maintenance application support second-tier applications development There is only so much work that you can do, and this pile of work is doomed to be shrinking over and over. there is only so much work that you can do and this pile of work is doomed to be shrinking over and over All the firms that operate in there, they're all exposed. all the firms that operate in there they're all exposed As I said previously, this has not been the place where EPAM was generally operating. as i said previously this has not been the place where epam was generally operating Where we operate largely is below the waterline, and this is where we see infinite backlog space. Our clients have been sitting on years' worth of queued work that previously they were not able to attempt. Product modernization, technical debt elimination, new product development, just higher velocity and productivity deliver more and more features for their own clients. A lot of this work was put on hold or was tabled for the reason it was too complex, too expensive, took a lot of time to deliver, or simply was not possible because of technology limitations. Now AI makes it possible. Edward Jones, they had a dormant mainframe authorization program that was in a slow-motion mode. Now with our AI/RUN platform and the plans, we out-competed incumbents, and now we are helping them to deliver, and now it is active. Where we operate largely is below the waterline, and this is where we see infinite backlog space. where we operate largely is below the waterline and this is where we see infinite backlog space Our clients have been sitting on years' worth of queued work that previously they were not able to attempt. our clients have been sitting on years' worth of queued work that previously they were not able to attempt Product modernization, technical debt elimination, new product development, just higher velocity and productivity deliver more and more features for their own clients. product modernization technical debt elimination new product development just higher velocity and productivity deliver more and more features for their own clients A lot of this work was put on hold or was tabled for the reason it was too complex, too expensive, took a lot of time to deliver, or simply was not possible because of technology limitations. a lot of this work was put on hold or was tabled for the reason it was too complex too expensive took a lot of time to deliver or simply was not possible because of technology limitations Now AI makes it possible. now ai makes it possible Edward Jones, they had a dormant mainframe authorization program that was in a slow-motion mode. edward jones they had a dormant mainframe authorization program that was in a slow-motion mode Now with our AI/RUN platform and the plans, we out-competed incumbents, and now we are helping them to deliver, and now it is active. now with our ai/run platform and the plans we out-competed incumbents and now we are helping them to deliver and now it is active Baker Hughes, we are a strategic engineering partner for them and helping them to work on a variety of different strategic programs in the range from data products to field-level AI assistance across all of the operations. Nelnet, we came in, and we helped them to accelerate their velocity. We helped them to define the new ways of working. As we increased our velocity, they wanted to do more of that. They increased their expectations, how many new features they wanted to deliver, and we scaled our footprint. More speed, more demand. Firms built on fixed-demand where are competing to deliver the same shrinking amount of work for cheaper. Efficiency without growth is a race to the bottom, and EPAM has not been operating there. We live below the waterline. Baker Hughes, we are a strategic engineering partner for them and helping them to work on a variety of different strategic programs in the range from data products to field-level AI assistance across all of the operations. baker hughes we are a strategic engineering partner for them and helping them to work on a variety of different strategic programs in the range from data products to field-level ai assistance across all of the operations Nelnet, we came in, and we helped them to accelerate their velocity. nelnet we came in and we helped them to accelerate their velocity We helped them to define the new ways of working. we helped them to define the new ways of working As we increased our velocity, they wanted to do more of that. as we increased our velocity they wanted to do more of that They increased their expectations, how many new features they wanted to deliver, and we scaled our footprint. they increased their expectations how many new features they wanted to deliver and we scaled our footprint More speed, more demand. more speed more demand Firms built on fixed-demand where are competing to deliver the same shrinking amount of work for cheaper. firms built on fixed-demand where are competing to deliver the same shrinking amount of work for cheaper Efficiency without growth is a race to the bottom, and EPAM has not been operating there. efficiency without growth is a race to the bottom and epam has not been operating there We live below the waterline. we live below the waterline Every time we get faster, clients are attempting to do more, and that's today's picture of demand. Now let's talk about what's coming next. Everything that we are building today, the agentic ecosystems, the agents orchestration, the enterprise hardening, that's the infrastructure that autonomous agents will require in future. Clients are paying for agentic delivery today and tomorrow it becomes the autonomous layer. Moreover, these autonomous agents, in the first place, will be attacking this top of the iceberg that I showed on the previous slide. Lower complexity, lower stakes work where we have not been operating, and this is where we can actually enter there as agents and agentic platform builders, exactly the type of complex engineering work that we've been famous for, and we can enter there as builders, not as incumbents that are protecting the margins. Every time we get faster, clients are attempting to do more, and that's today's picture of demand. every time we get faster clients are attempting to do more and that's today's picture of demand Now let's talk about what's coming next. now let's talk about what's coming next Everything that we are building today, the agentic ecosystems, the agents orchestration, the enterprise hardening, that's the infrastructure that autonomous agents will require in future. everything that we are building today the agentic ecosystems the agents orchestration the enterprise hardening that's the infrastructure that autonomous agents will require in future Clients are paying for agentic delivery today and tomorrow it becomes the autonomous layer. clients are paying for agentic delivery today and tomorrow it becomes the autonomous layer Moreover, these autonomous agents, in the first place, will be attacking this top of the iceberg that I showed on the previous slide. moreover these autonomous agents in the first place will be attacking this top of the iceberg that i showed on the previous slide Lower complexity, lower stakes work where we have not been operating, and this is where we can actually enter there as agents and agentic platform builders, exactly the type of complex engineering work that we've been famous for, and we can enter there as builders, not as incumbents that are protecting the margins. lower complexity lower stakes work where we have not been operating and this is where we can actually enter there as agents and agentic platform builders exactly the type of complex engineering work that we've been famous for and we can enter there as builders not as incumbents that are protecting the margins Let me repeat the four key takeaways and the four points that we started from. Enterprise complexity is growing. Every layer adds another, and demand for complex engineering is infinite. Second, AI creates the new engineering discipline that is difficult to master, and engineering depth is our moat. Third, we are agents builders. We are agentic platforms builders. We are codifying delivery in new ways to accommodate agents-first mentality, and we are scaling a new type of engineering profile to run it. Fourth, the investment that we are making and the work that we're actually delivering today for our clients for agents, that's the foundation for autonomous enterprise that is coming tomorrow, and with every engagement, we are getting closer to it. I started with the question, if coding is largely solved, why do clients need EPAM? Coding was never a hard part. Let me repeat the four key takeaways and the four points that we started from. let me repeat the four key takeaways and the four points that we started from Enterprise complexity is growing. enterprise complexity is growing Every layer adds another, and demand for complex engineering is infinite. every layer adds another and demand for complex engineering is infinite Second, AI creates the new engineering discipline that is difficult to master, and engineering depth is our moat. second ai creates the new engineering discipline that is difficult to master and engineering depth is our moat Third, we are agents builders. third we are agents builders We are agentic platforms builders. we are agentic platforms builders We are codifying delivery in new ways to accommodate agents-first mentality, and we are scaling a new type of engineering profile to run it. we are codifying delivery in new ways to accommodate agents-first mentality and we are scaling a new type of engineering profile to run it Fourth, the investment that we are making and the work that we're actually delivering today for our clients for agents, that's the foundation for autonomous enterprise that is coming tomorrow, and with every engagement, we are getting closer to it. fourth the investment that we are making and the work that we're actually delivering today for our clients for agents that's the foundation for autonomous enterprise that is coming tomorrow and with every engagement we are getting closer to it I started with the question, if coding is largely solved, why do clients need EPAM? i started with the question if coding is largely solved why do clients need epam Coding was never a hard part. coding was never a hard part Software engineering was. The better AI gets at writing code, the more what we do matters. Now I want to show you the video, the client testimonial from Larry Fitzpatrick from OneMain Financial. Thank you. Software engineering was. software engineering was The better AI gets at writing code, the more what we do matters. the better ai gets at writing code the more what we do matters Now I want to show you the video, the client testimonial from Larry Fitzpatrick from OneMain Financial. now i want to show you the video the client testimonial from larry fitzpatrick from onemain financial Thank you. thank you

Speaker 20: Hi, I'm Larry Fitzpatrick, CTO at OneMain Financial. OneMain is the leader in offering non-prime consumers responsible access to credit. We offer hardworking Americans personalized lending solutions, including personal loans, auto loans, and credit cards. We operate across 48 states, online, and in 1,300 branch locations. I lead our technology strategy and the teams building the digital data and core platforms behind our growth. I joined six years ago after AWS, and I've spent my career scaling technology organizations at the intersection of innovation and execution. In 2023, we made a deliberate decision that generative AI would change our industry, and we would adopt it responsibly. We started with optimizing our guardrails for the unique risks of gen AI so teams could move with confidence. One of several strategic opportunities we are focused on is our product development and operations life cycle. Hi, I'm Larry Fitzpatrick, CTO at OneMain Financial. hi i'm larry fitzpatrick cto at onemain financial OneMain is the leader in offering non-prime consumers responsible access to credit. onemain is the leader in offering non-prime consumers responsible access to credit We offer hardworking Americans personalized lending solutions, including personal loans, auto loans, and credit cards. we offer hardworking americans personalized lending solutions including personal loans auto loans and credit cards We operate across 48 states, online, and in 1,300 branch locations. we operate across 48 states online and in 1,300 branch locations I lead our technology strategy and the teams building the digital data and core platforms behind our growth. i lead our technology strategy and the teams building the digital data and core platforms behind our growth I joined six years ago after AWS, and I've spent my career scaling technology organizations at the intersection of innovation and execution. i joined six years ago after aws and i've spent my career scaling technology organizations at the intersection of innovation and execution In 2023, we made a deliberate decision that generative AI would change our industry, and we would adopt it responsibly. in 2023 we made a deliberate decision that generative ai would change our industry and we would adopt it responsibly We started with optimizing our guardrails for the unique risks of gen AI so teams could move with confidence. we started with optimizing our guardrails for the unique risks of gen ai so teams could move with confidence One of several strategic opportunities we are focused on is our product development and operations life cycle. one of several strategic opportunities we are focused on is our product development and operations life cycle Despite rolling out tools to teams, adoption was uneven. We met with many potential partners. Most sold slides and could not demonstrate performance. EPAM showed us how they were already working this way inside their own teams for over two years. We chose a partner who had done it, not just described it. Late last year, we engaged EPAM to work with the organization. It spans about 100 teams across the full product development and operations life cycle from product strategy and design through build, release, and run. EPAM didn't bring us a point solution. They brought an end-to-end system, a clear methodology, a working platform, and experienced practitioners who operate as one team. We started with structure. Their SDLC maturity model gave us a simple progression, AI enabled to AI engaged to AI native. On the platform side, we defined an AI agentic ecosystem tailored to our environment. Despite rolling out tools to teams, adoption was uneven. despite rolling out tools to teams adoption was uneven We met with many potential partners. we met with many potential partners Most sold slides and could not demonstrate performance. most sold slides and could not demonstrate performance EPAM showed us how they were already working this way inside their own teams for over two years. We chose a partner who had done it, not just described it. epam showed us how they were already working this way inside their own teams for over two years. we chose a partner who had done it not just described it Late last year, we engaged EPAM to work with the organization. late last year we engaged epam to work with the organization It spans about 100 teams across the full product development and operations life cycle from product strategy and design through build, release, and run. it spans about 100 teams across the full product development and operations life cycle from product strategy and design through build release and run EPAM didn't bring us a point solution. epam didn't bring us a point solution They brought an end-to-end system, a clear methodology, a working platform, and experienced practitioners who operate as one team. they brought an end-to-end system a clear methodology a working platform and experienced practitioners who operate as one team We started with structure. we started with structure Their SDLC maturity model gave us a simple progression, AI enabled to AI engaged to AI native. their sdlc maturity model gave us a simple progression ai enabled to ai engaged to ai native On the platform side, we defined an AI agentic ecosystem tailored to our environment. on the platform side we defined an ai agentic ecosystem tailored to our environment EPAM deployed their AI/RUN Agentic platform, and we integrated it into our stack. SSO, Jira, Confluence, Git. The tools meet our teams where they already work. We are still mid-journey, but engagement across our teams has exceeded expectations. The energy is real, and it is translating into meaningful results. This is a journey, not a destination, and we've accelerated greatly partnering with EPAM. EPAM deployed their AI/RUN Agentic platform, and we integrated it into our stack. epam deployed their ai/run agentic platform and we integrated it into our stack SSO, Jira, Confluence, Git. sso jira confluence git The tools meet our teams where they already work. the tools meet our teams where they already work We are still mid-journey, but engagement across our teams has exceeded expectations. we are still mid-journey but engagement across our teams has exceeded expectations The energy is real, and it is translating into meaningful results. the energy is real and it is translating into meaningful results This is a journey, not a destination, and we've accelerated greatly partnering with EPAM. this is a journey not a destination and we've accelerated greatly partnering with epam

Speaker 27: Good morning, everyone, and thank you once again for joining our Investor Day. My name is Nir Kaldero. I'm EPAM Chief Data and AI Strategist, and I'm on stage with great friend of mine, Eli. Good morning, everyone, and thank you once again for joining our Investor Day. good morning everyone and thank you once again for joining our investor day My name is Nir Kaldero. my name is nir kaldero I'm EPAM Chief Data and AI Strategist, and I'm on stage with great friend of mine, Eli. i'm epam chief data and ai strategist and i'm on stage with great friend of mine eli

Speaker 12: Eli Feldman, CTO. Eli Feldman, CTO. eli feldman cto

Speaker 27: Together we lead our enterprise AI transformation agenda on the business side. Today, we want to show you how we help our clients accelerate their journey towards an AI native enterprise through robust offering portfolio, differentiated delivery playbook, and end-to-end capabilities. Our goal is simple. We want to demonstrate not just what AI can really do, but why EPAM is uniquely positioned to win in this era of AI native business transformation. We will walk you through four core areas around AI business transformation. The first one, how AI native transformation is reshaping business innovation and operations, and how EPAM accelerate the journey with meaningful impact and growing book of business. Second, how our unique AI/RUN transform playbook turns strategy into measurable business outcome. Third, how strategically we expand our service mix to support and lead the next wave of AI adoption to successfully support our clients. Together we lead our enterprise AI transformation agenda on the business side. together we lead our enterprise ai transformation agenda on the business side Today, we want to show you how we help our clients accelerate their journey towards an AI native enterprise through robust offering portfolio, differentiated delivery playbook, and end-to-end capabilities. today we want to show you how we help our clients accelerate their journey towards an ai native enterprise through robust offering portfolio differentiated delivery playbook and end-to-end capabilities Our goal is simple. our goal is simple We want to demonstrate not just what AI can really do, but why EPAM is uniquely positioned to win in this era of AI native business transformation. we want to demonstrate not just what ai can really do but why epam is uniquely positioned to win in this era of ai native business transformation We will walk you through four core areas around AI business transformation. we will walk you through four core areas around ai business transformation The first one, how AI native transformation is reshaping business innovation and operations, and how EPAM accelerate the journey with meaningful impact and growing book of business. the first one how ai native transformation is reshaping business innovation and operations and how epam accelerate the journey with meaningful impact and growing book of business Second, how our unique AI/RUN transform playbook turns strategy into measurable business outcome. second how our unique ai/run transform playbook turns strategy into measurable business outcome Third, how strategically we expand our service mix to support and lead the next wave of AI adoption to successfully support our clients. third how strategically we expand our service mix to support and lead the next wave of ai adoption to successfully support our clients Lastly, how are our clients' biggest AI challenges driving long-term structural growth tailwind for EPAM for both business and engineering altogether? Let's dive in. Lastly, how are our clients' biggest AI challenges driving long-term structural growth tailwind for EPAM for both business and engineering altogether? lastly how are our clients' biggest ai challenges driving long-term structural growth tailwind for epam for both business and engineering altogether Let's dive in. let's dive in

Speaker 12: Thank you, Nir. We see this space transforming approximately along the same ways that Dima and Adam just described. There is maturity levels, there are stages, which organizations go through. The most foundational stage is start optimizing current operations. Easy place to start, but that requires a very meaningful foundation. Adam and Dima were talking about the foundation in engineering. That is a critical ingredient. Must be there. This is not your grandfather's business intelligence capabilities. These are foundational platforms and capabilities that need to be put in place all the way from engineering to data platforms to business capabilities to enable that. Once we solve that aspect of the challenge with our clients, then we can actually start transitioning to building business functions. Now, to make it very clear, this is not about just bottom up. Thank you, Nir. thank you nir We see this space transforming approximately along the same ways that Dima and Adam just described. we see this space transforming approximately along the same ways that dima and adam just described There is maturity levels, there are stages, which organizations go through. there is maturity levels there are stages which organizations go through The most foundational stage is start optimizing current operations. the most foundational stage is start optimizing current operations Easy place to start, but that requires a very meaningful foundation. easy place to start but that requires a very meaningful foundation Adam and Dima were talking about the foundation in engineering. adam and dima were talking about the foundation in engineering That is a critical ingredient. that is a critical ingredient Must be there. must be there This is not your grandfather's business intelligence capabilities. this is not your grandfather's business intelligence capabilities These are foundational platforms and capabilities that need to be put in place all the way from engineering to data platforms to business capabilities to enable that. these are foundational platforms and capabilities that need to be put in place all the way from engineering to data platforms to business capabilities to enable that Once we solve that aspect of the challenge with our clients, then we can actually start transitioning to building business functions. once we solve that aspect of the challenge with our clients then we can actually start transitioning to building business functions Now, to make it very clear, this is not about just bottom up. now to make it very clear this is not about just bottom up The bottom up is sort of the foundational and technology enablement. It is critically important, but that's not the only pathway. The other one is the top-down, understanding the business case, understanding what we're actually optimizing in the business. We'll go through some of the examples. Once we figure out that initial optimization space, well, we can now focus on growing the capabilities, running maybe even semi-autonomously the capabilities that these organizations have end to end. Once we capture all of this intelligence from the business process and the capabilities and the data assets and governance that is put in place to run that capability, then we can start identifying these new business opportunities for our clients, working with them together to bring that to the market. I'll give you two examples of work that we have done with our partners, with our clients. The bottom up is sort of the foundational and technology enablement. the bottom up is sort of the foundational and technology enablement It is critically important, but that's not the only pathway. it is critically important but that's not the only pathway The other one is the top-down, understanding the business case, understanding what we're actually optimizing in the business. the other one is the top-down understanding the business case understanding what we're actually optimizing in the business We'll go through some of the examples. we'll go through some of the examples Once we figure out that initial optimization space, well, we can now focus on growing the capabilities, running maybe even semi-autonomously the capabilities that these organizations have end to end. once we figure out that initial optimization space well we can now focus on growing the capabilities running maybe even semi-autonomously the capabilities that these organizations have end to end Once we capture all of this intelligence from the business process and the capabilities and the data assets and governance that is put in place to run that capability, then we can start identifying these new business opportunities for our clients, working with them together to bring that to the market. once we capture all of this intelligence from the business process and the capabilities and the data assets and governance that is put in place to run that capability then we can start identifying these new business opportunities for our clients working with them together to bring that to the market I'll give you two examples of work that we have done with our partners, with our clients. i'll give you two examples of work that we have done with our partners with our clients Critically important, each one of those started pretty much in the same place, the foundation. Cannot skip that. Have to enable foundation. Have to have the right engineering in place, have the right data platforms in place, the governance, the observability, all of these capabilities just to start even within a simple business process optimization. Once you have all of that data, well, all of a sudden, you can actually see how you can start optimizing, how can you build agentic AI around the business process and start optimizing. In the first case with a global cosmetic manufacturer, that first business case was demand prediction. We wanted to predict what actually sells in stores. We did that. The only challenge is simple if you know the demand, but you don't have the supply, you didn't really solve the problem. The business is not really benefiting. Critically important, each one of those started pretty much in the same place, the foundation. critically important each one of those started pretty much in the same place the foundation Cannot skip that. cannot skip that Have to enable foundation. have to enable foundation Have to have the right engineering in place, have the right data platforms in place, the governance, the observability, all of these capabilities just to start even within a simple business process optimization. have to have the right engineering in place have the right data platforms in place the governance the observability all of these capabilities just to start even within a simple business process optimization Once you have all of that data, well, all of a sudden, you can actually see how you can start optimizing, how can you build agentic AI around the business process and start optimizing. once you have all of that data well all of a sudden you can actually see how you can start optimizing how can you build agentic ai around the business process and start optimizing In the first case with a global cosmetic manufacturer, that first business case was demand prediction. in the first case with a global cosmetic manufacturer that first business case was demand prediction We wanted to predict what actually sells in stores. we wanted to predict what actually sells in stores We did that. The only challenge is simple if you know the demand, but you don't have the supply, you didn't really solve the problem. we did that. the only challenge is simple if you know the demand but you don't have the supply you didn't really solve the problem The business is not really benefiting. the business is not really benefiting Well, the obvious projection from there was let's try to figure the supply. The compounding problem, because you need to figure out the supply from the manufacturing process or maybe even before that all the way to when the product hits the store, is actually a compound data problem that is much more significant than any one of the individual elements. Just to give you a sense from a supply chain economic impact perspective within this organization, a weekly 100% risk reduction in this company from an economic impact perspective. Sales versus costs is about $16 million a week. In the past, before any of this was implemented, humans looking through dashboards again that old fathers, grandfathers sort of BI system, dashboards and reports and stuff like that could solve 30%. It's meaningful. Well, the obvious projection from there was let's try to figure the supply. well the obvious projection from there was let's try to figure the supply The compounding problem, because you need to figure out the supply from the manufacturing process or maybe even before that all the way to when the product hits the store, is actually a compound data problem that is much more significant than any one of the individual elements. the compounding problem because you need to figure out the supply from the manufacturing process or maybe even before that all the way to when the product hits the store is actually a compound data problem that is much more significant than any one of the individual elements Just to give you a sense from a supply chain economic impact perspective within this organization, a weekly 100% risk reduction in this company from an economic impact perspective. just to give you a sense from a supply chain economic impact perspective within this organization a weekly 100% risk reduction in this company from an economic impact perspective Sales versus costs is about $16 million a week. sales versus costs is about $16 million a week In the past, before any of this was implemented, humans looking through dashboards again that old fathers, grandfathers sort of BI system, dashboards and reports and stuff like that could solve 30%. in the past before any of this was implemented humans looking through dashboards again that old fathers grandfathers sort of bi system dashboards and reports and stuff like that could solve 30% It's meaningful. it's meaningful $5 million in economic impact they could have solved it. There's the long tail. When we started introducing the capability and sort of integrating all of the data together and working with the supply chain organization to figure out their value stream business process and all of that, we realized that about 50% of what AI actually recommends within the 30% slice still is very much consistent with what the organization actually was doing so far. Excellent result. It actually recommended the rest and almost closed the entire risk gap of the $16 million a year. A week. Sorry. This opened another interesting conversation. As Dima and Adam were saying, Dima was saying about sort of SaaS platforms and package capabilities and stuff like that. $5 million in economic impact they could have solved it. $5 million in economic impact they could have solved it There's the long tail. there's the long tail When we started introducing the capability and sort of integrating all of the data together and working with the supply chain organization to figure out their value stream business process and all of that, we realized that about 50% of what AI actually recommends within the 30% slice still is very much consistent with what the organization actually was doing so far. when we started introducing the capability and sort of integrating all of the data together and working with the supply chain organization to figure out their value stream business process and all of that we realized that about 50% of what ai actually recommends within the 30% slice still is very much consistent with what the organization actually was doing so far Excellent result. excellent result It actually recommended the rest and almost closed the entire risk gap of the $16 million a year. it actually recommended the rest and almost closed the entire risk gap of the $16 million a year A week. a week Sorry. sorry This opened another interesting conversation. this opened another interesting conversation As Dima and Adam were saying, Dima was saying about sort of SaaS platforms and package capabilities and stuff like that. as dima and adam were saying dima was saying about sort of saas platforms and package capabilities and stuff like that You see, vast majority of organizations out there, manufacturing organizations, supply chain organizations, CPG, and all of that, they have to rely on packaged supply chain tools because building a custom supply chain implementation across the board is extremely expensive. In the past, there was no ROI for that whatsoever. The largest supply chain organizations maybe, but most organizations could not. Now, the moment we solve the supply chain from manufacturing to store, all of a sudden they say, "Well, we have another tail of that problem. How about from the manufacturing end to the warehouse to the ingredients?" They had another packaged that was solving that, but the two were not really connected. They would manufacture one thing. Demand is something completely different. They optimize for that risk, sort of there is massive problem in between. You see, vast majority of organizations out there, manufacturing organizations, supply chain organizations, CPG, and all of that, they have to rely on packaged supply chain tools because building a custom supply chain implementation across the board is extremely expensive. you see vast majority of organizations out there manufacturing organizations supply chain organizations cpg and all of that they have to rely on packaged supply chain tools because building a custom supply chain implementation across the board is extremely expensive In the past, there was no ROI for that whatsoever. in the past there was no roi for that whatsoever The largest supply chain organizations maybe, but most organizations could not. the largest supply chain organizations maybe but most organizations could not Now, the moment we solve the supply chain from manufacturing to store, all of a sudden they say, "Well, we have another tail of that problem. now the moment we solve the supply chain from manufacturing to store all of a sudden they say "well we have another tail of that problem How about from the manufacturing end to the warehouse to the ingredients?" They had another packaged that was solving that, but the two were not really connected. how about from the manufacturing end to the warehouse to the ingredients?" they had another packaged that was solving that but the two were not really connected They would manufacture one thing. they would manufacture one thing Demand is something completely different. demand is something completely different They optimize for that risk, sort of there is massive problem in between. they optimize for that risk sort of there is massive problem in between Now, the implementation of that end-to-end supply chain, custom-built for that organization all of a sudden is a viable alternative to several complex integrations off-the-shelf tools, SaaS, platforms, et cetera. All of a sudden, we're actually capable of solving a significantly more meaningful business problem for the organization while leveraging everything that we have been talking about so far in terms of technology enablement and data enablement and governance, et cetera. Another observation that you sort of see on the slide, this field is continuously expanding. You prove one case, not prototype. Prove one case in production. Organization actually seeing economic impact. All of a sudden, well, we have this other business case. Another business case. And then it's expanding pretty much exponentially in that case, even within an individual organization. Now, the implementation of that end-to-end supply chain, custom-built for that organization all of a sudden is a viable alternative to several complex integrations off-the-shelf tools, SaaS, platforms, et cetera. now the implementation of that end-to-end supply chain custom-built for that organization all of a sudden is a viable alternative to several complex integrations off-the-shelf tools saas platforms et cetera All of a sudden, we're actually capable of solving a significantly more meaningful business problem for the organization while leveraging everything that we have been talking about so far in terms of technology enablement and data enablement and governance, et cetera. all of a sudden we're actually capable of solving a significantly more meaningful business problem for the organization while leveraging everything that we have been talking about so far in terms of technology enablement and data enablement and governance et cetera Another observation that you sort of see on the slide, this field is continuously expanding. another observation that you sort of see on the slide this field is continuously expanding You prove one case, not prototype. you prove one case not prototype Prove one case in production. prove one case in production Organization actually seeing economic impact. organization actually seeing economic impact All of a sudden, well, we have this other business case. all of a sudden well we have this other business case Another business case. another business case And then it's expanding pretty much exponentially in that case, even within an individual organization. and then it's expanding pretty much exponentially in that case even within an individual organization AI enables that because all of a sudden implementation is cheaper, so you can actually leverage the same budget to do significantly more work. I would like to speak about another client. You would think that CPG, well, not regulated space, pretty easy. But the reality is risk-reward in regulated organizations. The next case is a major global pharma. In global pharma, the foundation was exactly the same as before. Build a foundation, build the data capabilities, build the engineering capabilities, solve a business use case. Once we have done that, this client actually designate as a strategic partner for the entire stream of work around AI. They said, "Okay, we have another major business problem. Clinical trials." Clinical trials, 1% of defects in clinical trials. AI enables that because all of a sudden implementation is cheaper, so you can actually leverage the same budget to do significantly more work. ai enables that because all of a sudden implementation is cheaper so you can actually leverage the same budget to do significantly more work I would like to speak about another client. i would like to speak about another client You would think that CPG, well, not regulated space, pretty easy. you would think that cpg well not regulated space pretty easy But the reality is risk-reward in regulated organizations. but the reality is risk-reward in regulated organizations The next case is a major global pharma. the next case is a major global pharma In global pharma, the foundation was exactly the same as before. in global pharma the foundation was exactly the same as before Build a foundation, build the data capabilities, build the engineering capabilities, solve a business use case. build a foundation build the data capabilities build the engineering capabilities solve a business use case Once we have done that, this client actually designate as a strategic partner for the entire stream of work around AI. once we have done that this client actually designate as a strategic partner for the entire stream of work around ai They said, "Okay, we have another major business problem. they said "okay we have another major business problem Clinical trials." Clinical trials, 1% of defects in clinical trials. clinical trials." clinical trials 1% of defects in clinical trials Just 1% of defects in that process cost the organization $28 million in economic impact because it delays drugs to market, like all of that stuff. Most of it is a top-line impact. It's not even optimization. It's not really even cost optimization. Now you, if you are able to solve even into the low double digits, in that case, you actually have a very meaningful top-line impact on that organization. Once this organization learn what actually existing setup means, then they are capable of understanding their assets. Now we know what our clients need. We can actually convert that into something that is significantly more meaningful. You have two examples here. Just 1% of defects in that process cost the organization $28 million in economic impact because it delays drugs to market, like all of that stuff. just 1% of defects in that process cost the organization $28 million in economic impact because it delays drugs to market like all of that stuff Most of it is a top-line impact. most of it is a top-line impact It's not even optimization. it's not even optimization It's not really even cost optimization. it's not really even cost optimization Now you, if you are able to solve even into the low double digits, in that case, you actually have a very meaningful top-line impact on that organization. now you if you are able to solve even into the low double digits in that case you actually have a very meaningful top-line impact on that organization Once this organization learn what actually existing setup means, then they are capable of understanding their assets. once this organization learn what actually existing setup means then they are capable of understanding their assets Now we know what our clients need. now we know what our clients need We can actually convert that into something that is significantly more meaningful. we can actually convert that into something that is significantly more meaningful You have two examples here. you have two examples here One is a multinational for consumer lawn and garden products. They actually leveraging all of the foundation and all of the capabilities that we have built in business optimization, said, "Well, we can go DTC, direct to consumer." Like, we couldn't do that before. We were selling through resellers, like, all of our life, now we can go direct to consumer. A clear business value that was enabled by AI as well as all of the other work that was done. Swiss Re, which you will actually hear much more details in the panel later on. They realized being a reinsurer, they realized that they actually sell data. Again, all of that foundation actually paid off and enabled a new line of business for them. One is a multinational for consumer lawn and garden products. They actually leveraging all of the foundation and all of the capabilities that we have built in business optimization, said, "Well, we can go DTC, direct to consumer." Like, we couldn't do that before. one is a multinational for consumer lawn and garden products. they actually leveraging all of the foundation and all of the capabilities that we have built in business optimization said "well we can go dtc direct to consumer." like we couldn't do that before We were selling through resellers, like, all of our life, now we can go direct to consumer. we were selling through resellers like all of our life now we can go direct to consumer A clear business value that was enabled by AI as well as all of the other work that was done. a clear business value that was enabled by ai as well as all of the other work that was done Swiss Re, which you will actually hear much more details in the panel later on. swiss re which you will actually hear much more details in the panel later on They realized being a reinsurer, they realized that they actually sell data. they realized being a reinsurer they realized that they actually sell data Again, all of that foundation actually paid off and enabled a new line of business for them. again all of that foundation actually paid off and enabled a new line of business for them The reality is that EPAM wins at the first stage. We help optimize because we deeply understand the technology, that sort of bottom-up enablement capabilities, the technology, the engineering, and the foundation that we can build to our clients with AI-native enablement of course. We win in growing and running the business for our clients because we can layer the rest of the pie from a business transformation perspective. We understand the people transformation, we understand the business, we understand the value streams, we understand the flows. Now we can actually layer the two together and significantly enable these organizations as well. We can leverage all of the deep agentic capabilities, all of our experience over the past 30 years building go-to-market capabilities for our clients, and actually enable them to create new set of businesses that they have that are AI-native. The reality is that EPAM wins at the first stage. the reality is that epam wins at the first stage We help optimize because we deeply understand the technology, that sort of bottom-up enablement capabilities, the technology, the engineering, and the foundation that we can build to our clients with AI-native enablement of course. we help optimize because we deeply understand the technology that sort of bottom-up enablement capabilities the technology the engineering and the foundation that we can build to our clients with ai-native enablement of course We win in growing and running the business for our clients because we can layer the rest of the pie from a business transformation perspective. we win in growing and running the business for our clients because we can layer the rest of the pie from a business transformation perspective We understand the people transformation, we understand the business, we understand the value streams, we understand the flows. we understand the people transformation we understand the business we understand the value streams we understand the flows Now we can actually layer the two together and significantly enable these organizations as well. now we can actually layer the two together and significantly enable these organizations as well We can leverage all of the deep agentic capabilities, all of our experience over the past 30 years building go-to-market capabilities for our clients, and actually enable them to create new set of businesses that they have that are AI-native. we can leverage all of the deep agentic capabilities all of our experience over the past 30 years building go-to-market capabilities for our clients and actually enable them to create new set of businesses that they have that are ai-native Nir, please give us the details on. Nir, please give us the details on. nir please give us the details on

Speaker 27: Thank you. Thank you. thank you

Speaker 12: Oh, sorry. Oh, sorry. oh sorry

Speaker 27: One more slide. One more slide. one more slide

Speaker 12: One more slide. Sorry. All of that is actually quite systemic. Adam showed the slide before and we work very closely with the technology organization obviously to enable these capabilities, where we have the blueprints for the technology enablement, the prompts, the sequences, the workflows from engineering perspective. We actually develop the same from a domain and industry expertise, so we come to the customer with, like, deep understanding of the value stream of what they actually need to solve from a business perspective, enabled by technology out of the box and we're capable of solving that. We understand that none of this is possible with individual contributors. One more slide. one more slide Sorry. sorry All of that is actually quite systemic. all of that is actually quite systemic Adam showed the slide before and we work very closely with the technology organization obviously to enable these capabilities, where we have the blueprints for the technology enablement, the prompts, the sequences, the workflows from engineering perspective. adam showed the slide before and we work very closely with the technology organization obviously to enable these capabilities where we have the blueprints for the technology enablement the prompts the sequences the workflows from engineering perspective We actually develop the same from a domain and industry expertise, so we come to the customer with, like, deep understanding of the value stream of what they actually need to solve from a business perspective, enabled by technology out of the box and we're capable of solving that. we actually develop the same from a domain and industry expertise so we come to the customer with like deep understanding of the value stream of what they actually need to solve from a business perspective enabled by technology out of the box and we're capable of solving that We understand that none of this is possible with individual contributors. we understand that none of this is possible with individual contributors We must build networks of experts to be able to solve these complex problems, and these are networks of experts that include, again, engineering is critically important, but people that understand people, change management, transformation, domain, industry, governance, and all of the other stuff that needs to be in place to make it work. Then the tools and the platforms that need to be in place to enable that. The time to market needs to be accelerated, so we have to come with some accelerators, some harnesses, some productized offerings to be able to make it faster and more effective for our clients. Now, Nir, please. Take us through some of the details. We must build networks of experts to be able to solve these complex problems, and these are networks of experts that include, again, engineering is critically important, but people that understand people, change management, transformation, domain, industry, governance, and all of the other stuff that needs to be in place to make it work. we must build networks of experts to be able to solve these complex problems and these are networks of experts that include again engineering is critically important but people that understand people change management transformation domain industry governance and all of the other stuff that needs to be in place to make it work Then the tools and the platforms that need to be in place to enable that. then the tools and the platforms that need to be in place to enable that The time to market needs to be accelerated, so we have to come with some accelerators, some harnesses, some productized offerings to be able to make it faster and more effective for our clients. the time to market needs to be accelerated so we have to come with some accelerators some harnesses some productized offerings to be able to make it faster and more effective for our clients Now, Nir, please. Take us through some of the details. now nir please take us through some of the details

Speaker 27: Thank you, Eli. Thank you, Eli. thank you eli

Speaker 12: Thank you. Thank you. thank you

Speaker 27: All right. Now let's talk how we are expanding our strategic capabilities to lead the next wave of AI adoption. Successful AI adoption comes down to three kind of like main pillar. Think about it as a three-legged stool. The first one is the data, which is the fuel and really the foundation for AI. The second one is technology, which is the environment and the infrastructure to really deploy AI and use it to scale. The third one is people, culture, and process, which is probably the most important pillar here, where you really want to make sure that what you built is adopted and then delivering the business value following the investment. Across these three, we are expanding our AI strategic service capabilities to help our clients transform at scale to ensure we stay ahead of the market and help them. All right. all right Now let's talk how we are expanding our strategic capabilities to lead the next wave of AI adoption. now let's talk how we are expanding our strategic capabilities to lead the next wave of ai adoption Successful AI adoption comes down to three kind of like main pillar. successful ai adoption comes down to three kind of like main pillar Think about it as a three-legged stool. think about it as a three-legged stool The first one is the data, which is the fuel and really the foundation for AI. the first one is the data which is the fuel and really the foundation for ai The second one is technology, which is the environment and the infrastructure to really deploy AI and use it to scale. the second one is technology which is the environment and the infrastructure to really deploy ai and use it to scale The third one is people, culture, and process, which is probably the most important pillar here, where you really want to make sure that what you built is adopted and then delivering the business value following the investment. the third one is people culture and process which is probably the most important pillar here where you really want to make sure that what you built is adopted and then delivering the business value following the investment Across these three, we are expanding our AI strategic service capabilities to help our clients transform at scale to ensure we stay ahead of the market and help them. across these three we are expanding our ai strategic service capabilities to help our clients transform at scale to ensure we stay ahead of the market and help them Let me walk you through these kind of like four areas of expansion. The first one, we are reshaping our consulting model into something entirely new. AI-native, verticalized consulting built with and for AI. This isn't just traditional advisory. We use AI to conduct consulting itself. Instead of slide decks, we deliver prompts. Instead of static artifacts, we enable small language models across evolving processes. Instead of isolated recommendations, we co-design simulations with agentic tools, and we really aspire to help business leader run scenario planning with AI agents in days and not weeks or months even. We deliver consulting also for AI, the practical building blocks that make AI successful in productions all the way from operating models, governance, responsible AI, cybersecurity, adoption programs, and value tracking. Our consulting proposition is built for one purpose, moving AI from experimentation to production at scale. Let me walk you through these kind of like four areas of expansion. let me walk you through these kind of like four areas of expansion The first one, we are reshaping our consulting model into something entirely new. the first one we are reshaping our consulting model into something entirely new AI-native, verticalized consulting built with and for AI. ai-native verticalized consulting built with and for ai This isn't just traditional advisory. this isn't just traditional advisory We use AI to conduct consulting itself. we use ai to conduct consulting itself Instead of slide decks, we deliver prompts. instead of slide decks we deliver prompts Instead of static artifacts, we enable small language models across evolving processes. instead of static artifacts we enable small language models across evolving processes Instead of isolated recommendations, we co-design simulations with agentic tools, and we really aspire to help business leader run scenario planning with AI agents in days and not weeks or months even. instead of isolated recommendations we co-design simulations with agentic tools and we really aspire to help business leader run scenario planning with ai agents in days and not weeks or months even We deliver consulting also for AI, the practical building blocks that make AI successful in productions all the way from operating models, governance, responsible AI, cybersecurity, adoption programs, and value tracking. we deliver consulting also for ai the practical building blocks that make ai successful in productions all the way from operating models governance responsible ai cybersecurity adoption programs and value tracking Our consulting proposition is built for one purpose, moving AI from experimentation to production at scale. our consulting proposition is built for one purpose moving ai from experimentation to production at scale The second one is we are building the future of business operations, as FB mentioned. We are experimenting with and plan to disrupt the market through an agentic-led business operations offering, where we design, build, and run high-end processes powered by agentic AI. This lets us expand our share of wallet, evolve our service mix, and grow our total addressable market through next gen managed services. The third one is where technology and domain expertise truly converge. We are building deep industry knowledge with strong AI capabilities and acumen all together. Through our proximity to clients, we are developing industry-specific data models, co-creating vertical ontologies with strategic partners, and assembling pre-built agentic workflows tailored to how industries run. The payoff for our client is simple. Faster AI deployment in their specific context with less risk and greater precision towards the ROI. The fourth one, we are evolving our accelerators. The second one is we are building the future of business operations, as FB mentioned. the second one is we are building the future of business operations as fb mentioned We are experimenting with and plan to disrupt the market through an agentic-led business operations offering, where we design, build, and run high-end processes powered by agentic AI. we are experimenting with and plan to disrupt the market through an agentic-led business operations offering where we design build and run high-end processes powered by agentic ai This lets us expand our share of wallet, evolve our service mix, and grow our total addressable market through next gen managed services. The third one is where technology and domain expertise truly converge. this lets us expand our share of wallet evolve our service mix and grow our total addressable market through next gen managed services. the third one is where technology and domain expertise truly converge We are building deep industry knowledge with strong AI capabilities and acumen all together. we are building deep industry knowledge with strong ai capabilities and acumen all together Through our proximity to clients, we are developing industry-specific data models, co-creating vertical ontologies with strategic partners, and assembling pre-built agentic workflows tailored to how industries run. through our proximity to clients we are developing industry-specific data models co-creating vertical ontologies with strategic partners and assembling pre-built agentic workflows tailored to how industries run The payoff for our client is simple. the payoff for our client is simple Faster AI deployment in their specific context with less risk and greater precision towards the ROI. faster ai deployment in their specific context with less risk and greater precision towards the roi The fourth one, we are evolving our accelerators. the fourth one we are evolving our accelerators We have been already expanding migVisor into an agentic-led migration platform. We also extending for quite long time DIAL as an agentic orchestration platform. Think about it building agents with prompts. You have the ability to deploy mixed frontier models and ensure that AI is really deployed at scale all the way with governance, security, and FinOps from the get-go and from the start. Together, these kind of like four capabilities position us to be ready and ahead of the market to deliver real measurable value for our clients. Let me close with why we believe AI is a long-term structural tailwind for EPAM. Real AI business transformation isn't really just about deploying models or tools. It demands business model reinvention. Think about it as the culture and the mindset shift that enables completely new ways of working. We have been already expanding migVisor into an agentic-led migration platform. we have been already expanding migvisor into an agentic-led migration platform We also extending for quite long time DIAL as an agentic orchestration platform. we also extending for quite long time dial as an agentic orchestration platform Think about it building agents with prompts. think about it building agents with prompts You have the ability to deploy mixed frontier models and ensure that AI is really deployed at scale all the way with governance, security, and FinOps from the get-go and from the start. you have the ability to deploy mixed frontier models and ensure that ai is really deployed at scale all the way with governance security and finops from the get-go and from the start Together, these kind of like four capabilities position us to be ready and ahead of the market to deliver real measurable value for our clients. together these kind of like four capabilities position us to be ready and ahead of the market to deliver real measurable value for our clients Let me close with why we believe AI is a long-term structural tailwind for EPAM. let me close with why we believe ai is a long-term structural tailwind for epam Real AI business transformation isn't really just about deploying models or tools. real ai business transformation isn't really just about deploying models or tools It demands business model reinvention. it demands business model reinvention Think about it as the culture and the mindset shift that enables completely new ways of working. think about it as the culture and the mindset shift that enables completely new ways of working Process reimagination, targeting the right workflows and designing AI enhanced experience. Data monetization and modernization, really breaking the silos, capturing new data, and building the architecture and the semantic layer for reusable real-time intelligence across the enterprise. Obviously other critical services and elements across the end-to-end AI innovation life cycle all the way from AI strategy to MLOps and AIOps. Think about it, this complex business transformation work stream also generating significant downstream investment in core technology and engineering demand to enable the foundation to run, deploy, and use AI at scale, which altogether, if you think, creating a significant opportunity for EPAM to lead in the market. The business transformation work and the technology work also deeply interconnected, and we see both of them are growing. Process reimagination, targeting the right workflows and designing AI enhanced experience. process reimagination targeting the right workflows and designing ai enhanced experience Data monetization and modernization, really breaking the silos, capturing new data, and building the architecture and the semantic layer for reusable real-time intelligence across the enterprise. data monetization and modernization really breaking the silos capturing new data and building the architecture and the semantic layer for reusable real-time intelligence across the enterprise Obviously other critical services and elements across the end-to-end AI innovation life cycle all the way from AI strategy to MLOps and AIOps. obviously other critical services and elements across the end-to-end ai innovation life cycle all the way from ai strategy to mlops and aiops Think about it, this complex business transformation work stream also generating significant downstream investment in core technology and engineering demand to enable the foundation to run, deploy, and use AI at scale, which altogether, if you think, creating a significant opportunity for EPAM to lead in the market. think about it this complex business transformation work stream also generating significant downstream investment in core technology and engineering demand to enable the foundation to run deploy and use ai at scale which altogether if you think creating a significant opportunity for epam to lead in the market The business transformation work and the technology work also deeply interconnected, and we see both of them are growing. the business transformation work and the technology work also deeply interconnected and we see both of them are growing We are uniquely positioned to deliver strategy and implementation simultaneously to enable the full deployment and full scale reinforced by our AI native talent and unique playbook. Our end-to-end capabilities is really and truly our competitive advantage. This is why we believe EPAM will continue to capture market share as AI accelerate globally. With that, let me conclude and have some kind of like key takeaway to leave you with. The first one is we are driving our clients' AI native business transformation at scale. Few great examples that Eli show on stage. We are leveraging our unique and proven AI run transform playbook on the business side to turn AI strategy into measurable business outcome. We are uniquely positioned to deliver strategy and implementation simultaneously to enable the full deployment and full scale reinforced by our AI native talent and unique playbook. we are uniquely positioned to deliver strategy and implementation simultaneously to enable the full deployment and full scale reinforced by our ai native talent and unique playbook Our end-to-end capabilities is really and truly our competitive advantage. our end-to-end capabilities is really and truly our competitive advantage This is why we believe EPAM will continue to capture market share as AI accelerate globally. this is why we believe epam will continue to capture market share as ai accelerate globally With that, let me conclude and have some kind of like key takeaway to leave you with. with that let me conclude and have some kind of like key takeaway to leave you with The first one is we are driving our clients' AI native business transformation at scale. the first one is we are driving our clients' ai native business transformation at scale Few great examples that Eli show on stage. few great examples that eli show on stage We are leveraging our unique and proven AI run transform playbook on the business side to turn AI strategy into measurable business outcome. we are leveraging our unique and proven ai run transform playbook on the business side to turn ai strategy into measurable business outcome

Speaker 12: We're expanding our service mix to unlock new opportunities while staying ahead of the market, to support our clients' AI adoption journeys. Our clients' biggest AI challenges create long-term structural growth tailwind for EPAM within both engineering and consulting strategy simultaneously. With that, it's my pleasure to introduce our next client testimonial from Guy-Laurent Arpino, Chief Information Officer of LDC. Thank you. We're expanding our service mix to unlock new opportunities while staying ahead of the market, to support our clients' AI adoption journeys. we're expanding our service mix to unlock new opportunities while staying ahead of the market to support our clients' ai adoption journeys Our clients' biggest AI challenges create long-term structural growth tailwind for EPAM within both engineering and consulting strategy simultaneously. our clients' biggest ai challenges create long-term structural growth tailwind for epam within both engineering and consulting strategy simultaneously With that, it's my pleasure to introduce our next client testimonial from Guy-Laurent Arpino, Chief Information Officer of LDC. with that it's my pleasure to introduce our next client testimonial from guy-laurent arpino chief information officer of ldc Thank you. thank you

Speaker 27: Thank you. Thank you. thank you

Speaker 2: My name is Ahmet Tezel, and I'm the Chief Innovation Officer at LivaNova. My role is to lead end-to-end innovation in the company. It was clear to me that we needed an external partner to help us out in creating a cloud platform and products that go with it, and I had experience with EPAM from a previous company, and it was a good experience. One of the challenges if you're an epilepsy patient is that you have to go to a physician's office about eight to 10 times in your first year post-implant. The reason is that you go there to get your device adjusted with respect to its parameters. Now, this is not easy for epilepsy patients because they're pediatric patients or if they're adult patients, they usually don't have a driver's license. It's a complicated task. My name is Ahmet Tezel, and I'm the Chief Innovation Officer at LivaNova. my name is ahmet tezel and i'm the chief innovation officer at livanova My role is to lead end-to-end innovation in the company. my role is to lead end-to-end innovation in the company It was clear to me that we needed an external partner to help us out in creating a cloud platform and products that go with it, and I had experience with EPAM from a previous company, and it was a good experience. it was clear to me that we needed an external partner to help us out in creating a cloud platform and products that go with it and i had experience with epam from a previous company and it was a good experience One of the challenges if you're an epilepsy patient is that you have to go to a physician's office about eight to 10 times in your first year post-implant. one of the challenges if you're an epilepsy patient is that you have to go to a physician's office about eight to 10 times in your first year post-implant The reason is that you go there to get your device adjusted with respect to its parameters. the reason is that you go there to get your device adjusted with respect to its parameters Now, this is not easy for epilepsy patients because they're pediatric patients or if they're adult patients, they usually don't have a driver's license. now this is not easy for epilepsy patients because they're pediatric patients or if they're adult patients they usually don't have a driver's license It's a complicated task. it's a complicated task On average, you travel more than 30 miles for each adjustment. Doing this in-house in a hospital setting is difficult. Now, there is a huge unmet need here where you can do this adjustment in a remote setting, where the physician can connect to the device remotely and talk to the patient and do the necessary adjustments. That's the program that we developed with EPAM, where EPAM was able to create for us and work with us a secure private cloud connected care system that enables physicians to connect to our products remotely and adjust the parameters of the patient's device remotely. I envision that we will continue to work with EPAM. We now have the first FDA approval for our first franchise, our epilepsy franchise, through the product that we developed together. On average, you travel more than 30 miles for each adjustment. on average you travel more than 30 miles for each adjustment Doing this in-house in a hospital setting is difficult. doing this in-house in a hospital setting is difficult Now, there is a huge unmet need here where you can do this adjustment in a remote setting, where the physician can connect to the device remotely and talk to the patient and do the necessary adjustments. now there is a huge unmet need here where you can do this adjustment in a remote setting where the physician can connect to the device remotely and talk to the patient and do the necessary adjustments That's the program that we developed with EPAM, where EPAM was able to create for us and work with us a secure private cloud connected care system that enables physicians to connect to our products remotely and adjust the parameters of the patient's device remotely. that's the program that we developed with epam where epam was able to create for us and work with us a secure private cloud connected care system that enables physicians to connect to our products remotely and adjust the parameters of the patient's device remotely I envision that we will continue to work with EPAM. i envision that we will continue to work with epam We now have the first FDA approval for our first franchise, our epilepsy franchise, through the product that we developed together. we now have the first fda approval for our first franchise our epilepsy franchise through the product that we developed together I envision that we will continue to work together as we expand the partnership into other business units that we have in the company. We have a broad neuromodulation franchise with different disease states that could benefit from cloud-connected care, and we also have a cardiopulmonary franchise that can certainly benefit from having a connected ecosystem for their devices. I envision that we will continue to work together with EPAM as we roll out our digital ambitions to our broad business units. I envision that we will continue to work together as we expand the partnership into other business units that we have in the company. i envision that we will continue to work together as we expand the partnership into other business units that we have in the company We have a broad neuromodulation franchise with different disease states that could benefit from cloud-connected care, and we also have a cardiopulmonary franchise that can certainly benefit from having a connected ecosystem for their devices. we have a broad neuromodulation franchise with different disease states that could benefit from cloud-connected care and we also have a cardiopulmonary franchise that can certainly benefit from having a connected ecosystem for their devices I envision that we will continue to work together with EPAM as we roll out our digital ambitions to our broad business units. i envision that we will continue to work together with epam as we roll out our digital ambitions to our broad business units

Speaker 6: That was clearly not Guy-Laurent. You know, it couldn't be an EPAM presentation if it wouldn't have some mistakes. The clicker works, so that's typically our problem, but now we switched off a video. You're going to see Guy-Laurent in a later stage probably instead of live and over, we're going to play that video. That was clearly not Guy-Laurent. that was clearly not guy-laurent You know, it couldn't be an EPAM presentation if it wouldn't have some mistakes. you know it couldn't be an epam presentation if it wouldn't have some mistakes The clicker works, so that's typically our problem, but now we switched off a video. the clicker works so that's typically our problem but now we switched off a video You're going to see Guy-Laurent in a later stage probably instead of live and over, we're going to play that video. you're going to see guy-laurent in a later stage probably instead of live and over we're going to play that video

Speaker 24: Excellent. We're now gonna turn to our question and answer session. I'm joined by FB and Elaina here for about the next 20 minutes, call it. Just a quick couple of points for those in the room. Just please raise your hand, wait for the mic to come to you, state your name and firm, and we will get to as many questions as we can. We also, of course, covered the overall strategic overview, our transformation, and then our AI native pieces of the business. We kindly ask to keep your questions tailored to those sections as we have much more coming up later in the afternoon, including our financial imperatives and multiyear outlook. With that, we'll go ahead and open it up. Excellent. excellent We're now gonna turn to our question and answer session. we're now gonna turn to our question and answer session I'm joined by FB and Elaina here for about the next 20 minutes, call it. i'm joined by fb and elaina here for about the next 20 minutes call it Just a quick couple of points for those in the room. just a quick couple of points for those in the room Just please raise your hand, wait for the mic to come to you, state your name and firm, and we will get to as many questions as we can. just please raise your hand wait for the mic to come to you state your name and firm and we will get to as many questions as we can We also, of course, covered the overall strategic overview, our transformation, and then our AI native pieces of the business. we also of course covered the overall strategic overview our transformation and then our ai native pieces of the business We kindly ask to keep your questions tailored to those sections as we have much more coming up later in the afternoon, including our financial imperatives and multiyear outlook. we kindly ask to keep your questions tailored to those sections as we have much more coming up later in the afternoon including our financial imperatives and multiyear outlook With that, we'll go ahead and open it up. with that we'll go ahead and open it up We'll take one here in the front. Mr. Bergin. We'll take one here in the front. we'll take one here in the front Mr. Bergin. mr bergin

Speaker 7: All right, thank you. Bryan Bergin from TD Cowen. Appreciate all the color you've given so far. I wanted to ask on the go-to-market transformation. Trying to understand really how material this change is for you. You've talked about a, like, a consulting-led approach in the past. What are you gonna be doing differently now? I think you also mentioned maybe potentially some client-facing personnel changing. Just talk about how you're gonna manage execution risk around that. All right, thank you. all right thank you Bryan Bergin from TD Cowen. bryan bergin from td cowen Appreciate all the color you've given so far. appreciate all the color you've given so far I wanted to ask on the go-to-market transformation. i wanted to ask on the go-to-market transformation Trying to understand really how material this change is for you. trying to understand really how material this change is for you You've talked about a, like, a consulting-led approach in the past. you've talked about a like a consulting-led approach in the past What are you gonna be doing differently now? what are you gonna be doing differently now I think you also mentioned maybe potentially some client-facing personnel changing. i think you also mentioned maybe potentially some client-facing personnel changing Just talk about how you're gonna manage execution risk around that. just talk about how you're gonna manage execution risk around that

Speaker 6: Let me go back a little bit. Bryan, good to see you, and thank you, thank you for that question. Let me go back a little bit about EPAM. EPAM was historically operating in a seller's market, right? If we created the capabilities because of the resource shortages, people were coming to us and it was very much us showcasing our capabilities. I think in the last years, we learned that it's much more of a buyer's market, which means that we need to be more proactively marketing our services to them and actually start creating a more targeted go-to-market motion backed by marketing. At the same time, the way how we managing our client relationships are also changing, and we started to make those changes probably in the last one or two years. Let me go back a little bit. let me go back a little bit Bryan, good to see you, and thank you, thank you for that question. bryan good to see you and thank you thank you for that question Let me go back a little bit about EPAM. let me go back a little bit about epam EPAM was historically operating in a seller's market, right? epam was historically operating in a seller's market right If we created the capabilities because of the resource shortages, people were coming to us and it was very much us showcasing our capabilities. if we created the capabilities because of the resource shortages people were coming to us and it was very much us showcasing our capabilities I think in the last years, we learned that it's much more of a buyer's market, which means that we need to be more proactively marketing our services to them and actually start creating a more targeted go-to-market motion backed by marketing. i think in the last years we learned that it's much more of a buyer's market which means that we need to be more proactively marketing our services to them and actually start creating a more targeted go-to-market motion backed by marketing At the same time, the way how we managing our client relationships are also changing, and we started to make those changes probably in the last one or two years. at the same time the way how we managing our client relationships are also changing and we started to make those changes probably in the last one or two years Very much focusing and becoming more client-centric and very much highlighting the way how we're solutioning with our clients. Also, clients right now increasingly more transforming how they're delivering their businesses, as Eli and Nir was talking about, and we need to provide help to them. Elaina, could you add something to this? Very much focusing and becoming more client-centric and very much highlighting the way how we're solutioning with our clients. very much focusing and becoming more client-centric and very much highlighting the way how we're solutioning with our clients Also, clients right now increasingly more transforming how they're delivering their businesses, as Eli and Nir was talking about, and we need to provide help to them. also clients right now increasingly more transforming how they're delivering their businesses as eli and nir was talking about and we need to provide help to them Elaina, could you add something to this? elaina could you add something to this

Speaker 11: Yeah. Thanks, Bryan. Good to see you. For sure there's a couple of things going on. As FB said, we have to go get more of the business than we've ever had to before. We're actually changing that go get motion not just to sell AI, but changing it with AI. There's a fair amount of training that's already happened. There's more in terms of sales enablement and sales training to come. Yes, I think that there will be some rotations in the field. I think that's natural and expected and, in fact, welcomed. One of the biggest changes that we've made this past year is really integrating the industry consulting groups, which were historically for us more of a standalone service line into our IBUs, into our industry business units. Yeah. yeah Thanks, Bryan. thanks bryan Good to see you. good to see you For sure there's a couple of things going on. for sure there's a couple of things going on As FB said, we have to go get more of the business than we've ever had to before. as fb said we have to go get more of the business than we've ever had to before We're actually changing that go get motion not just to sell AI, but changing it with AI. we're actually changing that go get motion not just to sell ai but changing it with ai There's a fair amount of training that's already happened. there's a fair amount of training that's already happened There's more in terms of sales enablement and sales training to come. there's more in terms of sales enablement and sales training to come Yes, I think that there will be some rotations in the field. yes i think that there will be some rotations in the field I think that's natural and expected and, in fact, welcomed. i think that's natural and expected and in fact welcomed One of the biggest changes that we've made this past year is really integrating the industry consulting groups, which were historically for us more of a standalone service line into our IBUs, into our industry business units. one of the biggest changes that we've made this past year is really integrating the industry consulting groups which were historically for us more of a standalone service line into our ibus into our industry business units What that's creating is sort of these high-velocity teams that I spoke about and that you heard about now. Is it a risk? Probably. Is it absolutely critical? Definitely. What that's creating is sort of these high-velocity teams that I spoke about and that you heard about now. what that's creating is sort of these high-velocity teams that i spoke about and that you heard about now Is it a risk? is it a risk Probably. probably Is it absolutely critical? is it absolutely critical Definitely. definitely

Speaker 24: One here in the front. Jason, please. One here in the front. one here in the front Jason, please. jason please

Speaker 17: Thank you. Jason Kupferberg from Wells Fargo. Really appreciate all the detail. I wanted to ask about the these full stack agentic engineers. Interesting new role sounds like. Tell us a little bit about the profile of these individuals. How many of them do you have today? How many of them you think you'll have in two or three years? Thank you. thank you Jason Kupferberg from Wells Fargo. jason kupferberg from wells fargo Really appreciate all the detail. really appreciate all the detail I wanted to ask about the these full stack agentic engineers. i wanted to ask about the these full stack agentic engineers Interesting new role sounds like. interesting new role sounds like Tell us a little bit about the profile of these individuals. tell us a little bit about the profile of these individuals How many of them do you have today? how many of them do you have today How many of them you think you'll have in two or three years? how many of them you think you'll have in two or three years

Speaker 6: Jason, good to see you. I think it's a really good question. Clearly, this is something which we are growing rapidly right now. We have very much focused on this space. You will hear probably in 1 hour or so from now from Sandra and Alexei how we actually creating, how we finding them in the organization, and what training program we are putting through that. Actually, this capability is growing really fast because that's the real focus area. What we're doing is we're identifying them. We are actually putting through them with a rapid pace of understanding it, and we probably in the last just 3 months, we just doubled the capacity of that capability or that headcount. This is something which is going to be our standard motion going forward. Jason, good to see you. jason good to see you I think it's a really good question. i think it's a really good question Clearly, this is something which we are growing rapidly right now. clearly this is something which we are growing rapidly right now We have very much focused on this space. we have very much focused on this space You will hear probably in 1 hour or so from now from Sandra and Alexei how we actually creating, how we finding them in the organization, and what training program we are putting through that. you will hear probably in 1 hour or so from now from sandra and alexei how we actually creating how we finding them in the organization and what training program we are putting through that Actually, this capability is growing really fast because that's the real focus area. actually this capability is growing really fast because that's the real focus area What we're doing is we're identifying them. what we're doing is we're identifying them We are actually putting through them with a rapid pace of understanding it, and we probably in the last just 3 months, we just doubled the capacity of that capability or that headcount. we are actually putting through them with a rapid pace of understanding it and we probably in the last just 3 months we just doubled the capacity of that capability or that headcount This is something which is going to be our standard motion going forward. this is something which is going to be our standard motion going forward In every discipline, every line of business, we are basically pushing our engineering teams, but even account managers and delivery managers or the sales team at how to adopt and how to use AI. Just two weeks ago, we launched quite an aggressive and pushy program to make sure that our salespeople, account managers are actually using agentic tools to not just deliver their account plans and solutions, but actually understand fully how to deliver these applications. This is ongoing effort. That's where our investments are going, and we believe this is what's going to differentiate us and going to allow us to really scale in the years to come. In every discipline, every line of business, we are basically pushing our engineering teams, but even account managers and delivery managers or the sales team at how to adopt and how to use AI. in every discipline every line of business we are basically pushing our engineering teams but even account managers and delivery managers or the sales team at how to adopt and how to use ai Just two weeks ago, we launched quite an aggressive and pushy program to make sure that our salespeople, account managers are actually using agentic tools to not just deliver their account plans and solutions, but actually understand fully how to deliver these applications. just two weeks ago we launched quite an aggressive and pushy program to make sure that our salespeople account managers are actually using agentic tools to not just deliver their account plans and solutions but actually understand fully how to deliver these applications This is ongoing effort. this is ongoing effort That's where our investments are going, and we believe this is what's going to differentiate us and going to allow us to really scale in the years to come. that's where our investments are going and we believe this is what's going to differentiate us and going to allow us to really scale in the years to come

Speaker 24: Thank you. We have one here in the front. Thank you. thank you We have one here in the front. we have one here in the front

Speaker 15: Thank you. James Faucette, Morgan Stanley. Thanks for putting this on today. I wanted to ask a little bit, as you change the engagement approach and sounds like some of the development approach, is that gonna necessitate also a change in the way that things are architected from the beginning? And how does that impact things like sales cycles and project scaling and that kind of thing? Thank you. Thank you. thank you James Faucette, Morgan Stanley. james faucette morgan stanley Thanks for putting this on today. thanks for putting this on today I wanted to ask a little bit, as you change the engagement approach and sounds like some of the development approach, is that gonna necessitate also a change in the way that things are architected from the beginning? i wanted to ask a little bit as you change the engagement approach and sounds like some of the development approach is that gonna necessitate also a change in the way that things are architected from the beginning And how does that impact things like sales cycles and project scaling and that kind of thing? and how does that impact things like sales cycles and project scaling and that kind of thing Thank you. thank you

Speaker 6: Good to see you. Absolutely it's changing. Actually, if you will, just a shameless plug, as you are in the audience, go after the session, we have a whole video actually explaining to you how we are using what we called AI factories in the sales process, how it's actually integrated in our RFP creation, RFP responses, which is really going to change the way we are going to market and actually sells our efforts. It is changing not just how we're selling, it's not just the way we are contracting. It is changing how we are architecting the solution, how we're putting together the solution itself. We will be talking about how we quality assure all the proposals and all the estimates using AI. Good to see you. good to see you Absolutely it's changing. absolutely it's changing Actually, if you will, just a shameless plug, as you are in the audience, go after the session, we have a whole video actually explaining to you how we are using what we called AI factories in the sales process, how it's actually integrated in our RFP creation, RFP responses, which is really going to change the way we are going to market and actually sells our efforts. actually if you will just a shameless plug as you are in the audience go after the session we have a whole video actually explaining to you how we are using what we called ai factories in the sales process how it's actually integrated in our rfp creation rfp responses which is really going to change the way we are going to market and actually sells our efforts It is changing not just how we're selling, it's not just the way we are contracting. it is changing not just how we're selling it's not just the way we are contracting It is changing how we are architecting the solution, how we're putting together the solution itself. it is changing how we are architecting the solution how we're putting together the solution itself We will be talking about how we quality assure all the proposals and all the estimates using AI. we will be talking about how we quality assure all the proposals and all the estimates using ai This is very much ingrained into our go-to-market motion, the way we delivering, the way we are go to market and actually how we build the solution and how we're using AI in every possible step where it's possible. Where it's not just possible, where we are able to figure out how to plug it in today. We're finding new and new ways, you know, every day. This is very much ingrained into our go-to-market motion, the way we delivering, the way we are go to market and actually how we build the solution and how we're using AI in every possible step where it's possible. this is very much ingrained into our go-to-market motion the way we delivering the way we are go to market and actually how we build the solution and how we're using ai in every possible step where it's possible Where it's not just possible, where we are able to figure out how to plug it in today. where it's not just possible where we are able to figure out how to plug it in today We're finding new and new ways, you know, every day. we're finding new and new ways you know every day

Speaker 24: Two over here. Please. Two over here. two over here Please. please

Speaker 8: Hi, it's Bryan Keane at Citi. Can you talk a little bit about going after that fixed demand, some of that work that you guys didn't do traditionally that was more labor arbitrage, how you guys can get into that market through AI, and how fast can you disrupt that market by coming in at different prices? Hi, it's Bryan Keane at Citi. hi it's bryan keane at citi Can you talk a little bit about going after that fixed demand, some of that work that you guys didn't do traditionally that was more labor arbitrage, how you guys can get into that market through AI, and how fast can you disrupt that market by coming in at different prices? can you talk a little bit about going after that fixed demand some of that work that you guys didn't do traditionally that was more labor arbitrage how you guys can get into that market through ai and how fast can you disrupt that market by coming in at different prices

Speaker 6: I think it's a good question. I think we had early indications that we had success in this space in the last months and weeks. We made many proposals in this area. It's probably too early to call a full success, but we see real promises in this area. We're going to, again, shameless plug, you're going to see some amazing videos and demonstrations behind you around how we're going after the manual testing space and how we're going after the intelligent operation space with AI. How we're helping that in this area. Also, we're going to start seeing capabilities, how we're actually doing BPO automations for some of our clients. I think it's a good question. i think it's a good question I think we had early indications that we had success in this space in the last months and weeks. i think we had early indications that we had success in this space in the last months and weeks We made many proposals in this area. we made many proposals in this area It's probably too early to call a full success, but we see real promises in this area. it's probably too early to call a full success but we see real promises in this area We're going to, again, shameless plug, you're going to see some amazing videos and demonstrations behind you around how we're going after the manual testing space and how we're going after the intelligent operation space with AI. we're going to again shameless plug you're going to see some amazing videos and demonstrations behind you around how we're going after the manual testing space and how we're going after the intelligent operation space with ai How we're helping that in this area. how we're helping that in this area Also, we're going to start seeing capabilities, how we're actually doing BPO automations for some of our clients. also we're going to start seeing capabilities how we're actually doing bpo automations for some of our clients Actually we have public case studies around it where our clients are starting to see real ROI, us replacing more traditional call center agents with AI-based solutions. How fast it's going to scale, it's probably early to tell, but we are seeing demand interest from our clients. Because we coming in with a very fresh point of view, we coming in with a new ways how we approaching it, with a new price point, a new way of delivering it, new way of taking advantage of AI to do knowledge transfer. This creates quite a buzz in our community. Actually we have public case studies around it where our clients are starting to see real ROI, us replacing more traditional call center agents with AI-based solutions. actually we have public case studies around it where our clients are starting to see real roi us replacing more traditional call center agents with ai-based solutions How fast it's going to scale, it's probably early to tell, but we are seeing demand interest from our clients. how fast it's going to scale it's probably early to tell but we are seeing demand interest from our clients Because we coming in with a very fresh point of view, we coming in with a new ways how we approaching it, with a new price point, a new way of delivering it, new way of taking advantage of AI to do knowledge transfer. because we coming in with a very fresh point of view we coming in with a new ways how we approaching it with a new price point a new way of delivering it new way of taking advantage of ai to do knowledge transfer This creates quite a buzz in our community. this creates quite a buzz in our community

Speaker 11: Can I? Can I? can i

Speaker 6: Yes, absolutely. Yes, absolutely. yes absolutely

Speaker 11: Just to maybe put a point, a fine point on it, for us, it's a transformation pitch. It is not a labor arbitrage optimization pitch, and all of the attendant things that go with it, including organizational design, platform architecture, et cetera. It's much more than just a labor arbitrage market capture opportunity. Just to maybe put a point, a fine point on it, for us, it's a transformation pitch. just to maybe put a point a fine point on it for us it's a transformation pitch It is not a labor arbitrage optimization pitch, and all of the attendant things that go with it, including organizational design, platform architecture, et cetera. it is not a labor arbitrage optimization pitch and all of the attendant things that go with it including organizational design platform architecture et cetera It's much more than just a labor arbitrage market capture opportunity. it's much more than just a labor arbitrage market capture opportunity

Speaker 24: One here in the front, then next to you. One here in the front, then next to you. one here in the front then next to you

Speaker 29: Thank you. This is Puneet from JPMorgan. As you pursue AI native SDLC, bring AI into SDLC, which changes the way you engage with your customers, talk to us about change management aspects, like from clients' perspective. Like, are they ready? Or more importantly, are their employees ready for these changes? Will, like, all the recent news flow around Anthropic and the development there in cloud and everything, has that changed their behavior in any way? Thank you. thank you This is Puneet from JP Morgan. this is puneet from jp morgan As you pursue AI native SDLC, bring AI into SDLC, which changes the way you engage with your customers, talk to us about change management aspects, like from clients' perspective. as you pursue ai native sdlc bring ai into sdlc which changes the way you engage with your customers talk to us about change management aspects like from clients' perspective Like, are they ready? like are they ready Or more importantly, are their employees ready for these changes? or more importantly are their employees ready for these changes Will, like, all the recent news flow around Anthropic and the development there in cloud and everything, has that changed their behavior in any way? will like all the recent news flow around anthropic and the development there in cloud and everything has that changed their behavior in any way

Speaker 6: I think, Puneet, great question. I think if I want to summarize it is a change management process. We're going engagement by engagement, project by project, and we're talking about thousands of engagements which we are migrating, which we are elevating in terms of maturity. Are our clients' employees ready? No. It's an opportunity for us. We are giving them education. We are giving them advice how to change organization, how to introduce new tools, how to actually go through this whole education coaching process. Most organizations just went out, as Dima and Adam talked about, went out and bought the tools, and they said, "Here you go. I think, Puneet, great question. i think puneet great question I think if I want to summarize it is a change management process. i think if i want to summarize it is a change management process We're going engagement by engagement, project by project, and we're talking about thousands of engagements which we are migrating, which we are elevating in terms of maturity. we're going engagement by engagement project by project and we're talking about thousands of engagements which we are migrating which we are elevating in terms of maturity Are our clients' employees ready? are our clients' employees ready No. no It's an opportunity for us. it's an opportunity for us We are giving them education. we are giving them education We are giving them advice how to change organization, how to introduce new tools, how to actually go through this whole education coaching process. we are giving them advice how to change organization how to introduce new tools how to actually go through this whole education coaching process Most organizations just went out, as Dima and Adam talked about, went out and bought the tools, and they said, "Here you go. most organizations just went out as dima and adam talked about went out and bought the tools and they said "here you go We expect you to be 15%-20% more efficient. You know, couple of months later, they found out that it's actually a J curve and their productivity kind of dropped. They said, "Okay, why don't I use some online resources? This is where you can read about it, and there are some forums." Nothing happened. This is the point where we are entering into the picture, where we are really start advising them and coaching them how to actually mature the engagement model. They are not ready. I think all the changes you are referencing, which is, Anthropic or, OpenAI, launch of Claude Code or Codex, this is only for the really mature clients and mature engineering teams. We expect you to be 15%-20% more efficient. we expect you to be 15%-20% more efficient You know, couple of months later, they found out that it's actually a J curve and their productivity kind of dropped. you know couple of months later they found out that it's actually a j curve and their productivity kind of dropped They said, "Okay, why don't I use some online resources? they said "okay why don't i use some online resources This is where you can read about it, and there are some forums." Nothing happened. this is where you can read about it and there are some forums." nothing happened This is the point where we are entering into the picture, where we are really start advising them and coaching them how to actually mature the engagement model. this is the point where we are entering into the picture where we are really start advising them and coaching them how to actually mature the engagement model They are not ready. they are not ready I think all the changes you are referencing, which is, Anthropic or, OpenAI, launch of Claude Code or Codex, this is only for the really mature clients and mature engineering teams. i think all the changes you are referencing which is anthropic or openai launch of claude code or codex this is only for the really mature clients and mature engineering teams If you just launch in a legacy code base in a brownfield, any of these tools, these tools go, you know, go wild, and they actually not going to create any productivity because you need the specs, because you need to describe the brownfield itself, the expectations, and you need to have the right tooling in place. It takes a while to adopt. It's a change process, and we see a multiyear adoption for the enterprises. If you just launch in a legacy code base in a brownfield, any of these tools, these tools go, you know, go wild, and they actually not going to create any productivity because you need the specs, because you need to describe the brownfield itself, the expectations, and you need to have the right tooling in place. if you just launch in a legacy code base in a brownfield any of these tools these tools go you know go wild and they actually not going to create any productivity because you need the specs because you need to describe the brownfield itself the expectations and you need to have the right tooling in place It takes a while to adopt. it takes a while to adopt It's a change process, and we see a multiyear adoption for the enterprises. it's a change process and we see a multiyear adoption for the enterprises

Speaker 24: I think we had one here, and then we'll go to the one over there. I think we had one here, and then we'll go to the one over there. i think we had one here and then we'll go to the one over there

Speaker 26: Thanks very much. This is Nate Svensson from Deutsche Bank. I'm gonna kinda build on Puneet's question here. I really like the slide with the three levels of AI adoption. I thought that was a useful heuristic. Sounds like most companies are on that first inconsistent and ad hoc usage stage of AI adoption. Your differentiation and moat is going from the second to third stage. I guess the question is, if most companies are in stage one today, how do you help them get to stage two to ultimately get to where you have the most competitive differentiation? Why are they gonna choose EPAM to go from stage one to stage two versus a different system integrator, other sort of competitor, and how do you maintain that client relationship as we continue to progress? Thanks very much. thanks very much This is Nate Svensson from Deutsche Bank. this is nate svensson from deutsche bank I'm gonna kinda build on Puneet's question here. i'm gonna kinda build on puneet's question here I really like the slide with the three levels of AI adoption. i really like the slide with the three levels of ai adoption I thought that was a useful heuristic. i thought that was a useful heuristic Sounds like most companies are on that first inconsistent and ad hoc usage stage of AI adoption. sounds like most companies are on that first inconsistent and ad hoc usage stage of ai adoption Your differentiation and moat is going from the second to third stage. your differentiation and moat is going from the second to third stage I guess the question is, if most companies are in stage one today, how do you help them get to stage two to ultimately get to where you have the most competitive differentiation? i guess the question is if most companies are in stage one today how do you help them get to stage two to ultimately get to where you have the most competitive differentiation Why are they gonna choose EPAM to go from stage one to stage two versus a different system integrator, other sort of competitor, and how do you maintain that client relationship as we continue to progress? why are they gonna choose epam to go from stage one to stage two versus a different system integrator other sort of competitor and how do you maintain that client relationship as we continue to progress

Speaker 6: Very good question. I think why they're going to choose EPAM, because we will go in and show you not just slide decks. This is the case where we're showing slide decks to you, but in most cases we are coming with real examples, real blueprints, real proof points, how you're going to get there, very practical. How can we actually go in there? It's very hands-on experience. Our clients are seeing that the leadership team who we have, the people on the field are really understand how to make this happen. This is the experience. Very good question. very good question I think why they're going to choose EPAM, because we will go in and show you not just slide decks. i think why they're going to choose epam because we will go in and show you not just slide decks This is the case where we're showing slide decks to you, but in most cases we are coming with real examples, real blueprints, real proof points, how you're going to get there, very practical. this is the case where we're showing slide decks to you but in most cases we are coming with real examples real blueprints real proof points how you're going to get there very practical How can we actually go in there? how can we actually go in there It's very hands-on experience. it's very hands-on experience Our clients are seeing that the leadership team who we have, the people on the field are really understand how to make this happen. our clients are seeing that the leadership team who we have the people on the field are really understand how to make this happen This is the experience. this is the experience When they talk to me, they actually kind of see on my computer, I'm running a Claude Code, and it's a very different discussions when the CEO really starts talking to them about the best way how to use in the enterprise for all the different purposes agentic tooling itself. It brings a level of credibility. Most organizations actually not even at level one. Most organizations are still level zero. They haven't purchased the tools yet because they never done the investments. It's just in the last six months when people really started to understand that this is really happening. Previously, based on all the different data points, people were kinda skeptical. Now skepticism is gone. They start investing. They, the only thing what they are able to do is go out and make those purchases. When they talk to me, they actually kind of see on my computer, I'm running a Claude Code, and it's a very different discussions when the CEO really starts talking to them about the best way how to use in the enterprise for all the different purposes agentic tooling itself. when they talk to me they actually kind of see on my computer i'm running a claude code and it's a very different discussions when the ceo really starts talking to them about the best way how to use in the enterprise for all the different purposes agentic tooling itself It brings a level of credibility. it brings a level of credibility Most organizations actually not even at level one. most organizations actually not even at level one Most organizations are still level zero. most organizations are still level zero They haven't purchased the tools yet because they never done the investments. they haven't purchased the tools yet because they never done the investments It's just in the last six months when people really started to understand that this is really happening. it's just in the last six months when people really started to understand that this is really happening Previously, based on all the different data points, people were kinda skeptical. previously based on all the different data points people were kinda skeptical Now skepticism is gone. now skepticism is gone They start investing. they start investing They, the only thing what they are able to do is go out and make those purchases. they the only thing what they are able to do is go out and make those purchases That's why probably the revenues of these companies are skyrocketing right now. The adoption is very, very difficult. We are going out with the blueprints, with the runbooks on how to make the transformation with the educational materials, understanding how to actually go through step-by-step the change process, understanding how to mature engagement by engagement, because it's not a top-down, I would say, big bang. It is happening. You have to do it project by project, going step by step, and as you are maturing these engagements, you can go to the next level. We have examples, and we can actually show how you're able to execute that in an organization such as EPAM at 60,000 people scale, and that's very unique. That's why probably the revenues of these companies are skyrocketing right now. that's why probably the revenues of these companies are skyrocketing right now The adoption is very, very difficult. the adoption is very very difficult We are going out with the blueprints, with the runbooks on how to make the transformation with the educational materials, understanding how to actually go through step-by-step the change process, understanding how to mature engagement by engagement, because it's not a top-down, I would say, big bang. we are going out with the blueprints with the runbooks on how to make the transformation with the educational materials understanding how to actually go through step-by-step the change process understanding how to mature engagement by engagement because it's not a top-down i would say big bang It is happening. it is happening You have to do it project by project, going step by step, and as you are maturing these engagements, you can go to the next level. you have to do it project by project going step by step and as you are maturing these engagements you can go to the next level We have examples, and we can actually show how you're able to execute that in an organization such as EPAM at 60,000 people scale, and that's very unique. we have examples and we can actually show how you're able to execute that in an organization such as epam at 60,000 people scale and that's very unique

Speaker 11: That's why they're called foundational services for us. That's why they're called foundational services for us. that's why they're called foundational services for us

Speaker 24: Let's go here, and then here. Let's go here, and then here. let's go here and then here

Speaker 16: Thanks. It's Jamie Friedman from Susquehanna. I was revisiting my notes from Dmitry's talk about the four reasons to need EPAM: enterprise complexity, engineering moat, agent building, autonomous enterprise. If I messed those up, I apologize. My question is, if those are the reasons to need EPAM currently, I'm wondering, does it change the relevance of the global delivery footprint, and does it potentially argue for a bigger on-site, on-shore presence? Thanks. thanks It's Jamie Friedman from Susquehanna. it's jamie friedman from susquehanna I was revisiting my notes from Dmitry's talk about the four reasons to need EPAM: enterprise complexity, engineering moat, agent building, autonomous enterprise. i was revisiting my notes from dmitry's talk about the four reasons to need epam enterprise complexity engineering moat agent building autonomous enterprise If I messed those up, I apologize. if i messed those up i apologize My question is, if those are the reasons to need EPAM currently, I'm wondering, does it change the relevance of the global delivery footprint, and does it potentially argue for a bigger on-site, on-shore presence? my question is if those are the reasons to need epam currently i'm wondering does it change the relevance of the global delivery footprint and does it potentially argue for a bigger on-site on-shore presence

Speaker 6: That's a great question. I think what we are seeing right now is our clients and enterprises, the same time they're trying to mature AI SDLC, mature the engagement model, mature the maturity what they're doing, same time they are executing in parallel other strategies, such as moving to GCCs in India or other locations. They're coming to us, how can they upskill their existing so-called legacy GCC with new skills? How can we help them to increase their internal efficiency? Just the other week, I was talking to our client when making this pitch. They are actually expressing their need that can you engage with EPAM, with the EPAM scale globally to tackle their own internal legacy. Their own legacy is not on-site. That's a great question. that's a great question I think what we are seeing right now is our clients and enterprises, the same time they're trying to mature AI SDLC, mature the engagement model, mature the maturity what they're doing, same time they are executing in parallel other strategies, such as moving to GCCs in India or other locations. i think what we are seeing right now is our clients and enterprises the same time they're trying to mature ai sdlc mature the engagement model mature the maturity what they're doing same time they are executing in parallel other strategies such as moving to gccs in india or other locations They're coming to us, how can they upskill their existing so-called legacy GCC with new skills? they're coming to us how can they upskill their existing so-called legacy gcc with new skills How can we help them to increase their internal efficiency? how can we help them to increase their internal efficiency Just the other week, I was talking to our client when making this pitch. just the other week i was talking to our client when making this pitch They are actually expressing their need that can you engage with EPAM, with the EPAM scale globally to tackle their own internal legacy. they are actually expressing their need that can you engage with epam with the epam scale globally to tackle their own internal legacy Their own legacy is not on-site. their own legacy is not on-site Their own legacy is it's a global footprint with different GCCs in different countries, starting from India to Spain to, in this case, it was Portugal and Slovakia. That's where engineering is happening today, and you need to meet your clients where their engineers are. For us, we don't foresee that, and actually later on, you are going to hear on the panel how we're seeing all these things play out in each and every different geographies where we are. Their own legacy is it's a global footprint with different GCCs in different countries, starting from India to Spain to, in this case, it was Portugal and Slovakia. their own legacy is it's a global footprint with different gccs in different countries starting from india to spain to in this case it was portugal and slovakia That's where engineering is happening today, and you need to meet your clients where their engineers are. that's where engineering is happening today and you need to meet your clients where their engineers are For us, we don't foresee that, and actually later on, you are going to hear on the panel how we're seeing all these things play out in each and every different geographies where we are. for us we don't foresee that and actually later on you are going to hear on the panel how we're seeing all these things play out in each and every different geographies where we are

Speaker 33: Surinder Thind with Jefferies. Following up an earlier question about the client journey and going from level one to two to three, and I think, FB, you mentioned that maybe a lot of them are even at level zero. Can you maybe talk about the propensity of clients to move away from level one in the sense that if the models continue to get better, right? We look at the journey over the last couple of years, would a client not want to continue to try and do more themselves, especially if the models continue to scale at the current pace? And are we in a situation where we have to wait until maybe there's a more maturing of the technology before clients move to level two and three? Or, or what gets them across that line? Because it just seems like industry demand remains relatively tepid. Surinder Thind with Jefferies. surinder thind with jefferies Following up an earlier question about the client journey and going from level one to two to three, and I think, FB, you mentioned that maybe a lot of them are even at level zero. following up an earlier question about the client journey and going from level one to two to three and i think fb you mentioned that maybe a lot of them are even at level zero Can you maybe talk about the propensity of clients to move away from level one in the sense that if the models continue to get better, right? can you maybe talk about the propensity of clients to move away from level one in the sense that if the models continue to get better right We look at the journey over the last couple of years, would a client not want to continue to try and do more themselves, especially if the models continue to scale at the current pace? we look at the journey over the last couple of years would a client not want to continue to try and do more themselves especially if the models continue to scale at the current pace And are we in a situation where we have to wait until maybe there's a more maturing of the technology before clients move to level two and three? and are we in a situation where we have to wait until maybe there's a more maturing of the technology before clients move to level two and three Or, or what gets them across that line? or or what gets them across that line Because it just seems like industry demand remains relatively tepid. because it just seems like industry demand remains relatively tepid

Speaker 6: Thank you very much. It's a good question. Okay, so I think the models are maturing very, very rapidly. We all know that the capabilities. Also the price point of the certain level of capability maturity is continuously dropping. For different business scenarios, business cases, you need different level of maturity. Depending on your price point of engineering, depending on the business case you would like to use AI for, right? There is different entry points. It might be possible that due to tokenomics, the today for one company this is affordable and or actually economical to deploy AI today, or some decides to wait a little bit later while the, let's say, the models mature or the cost drops because there's two things happening at the same time. Thank you very much. thank you very much It's a good question. it's a good question Okay, so I think the models are maturing very, very rapidly. okay so i think the models are maturing very very rapidly We all know that the capabilities. we all know that the capabilities Also the price point of the certain level of capability maturity is continuously dropping. also the price point of the certain level of capability maturity is continuously dropping For different business scenarios, business cases, you need different level of maturity. for different business scenarios business cases you need different level of maturity Depending on your price point of engineering, depending on the business case you would like to use AI for, right? depending on your price point of engineering depending on the business case you would like to use ai for right There is different entry points. there is different entry points It might be possible that due to tokenomics, the today for one company this is affordable and or actually economical to deploy AI today, or some decides to wait a little bit later while the, let's say, the models mature or the cost drops because there's two things happening at the same time. it might be possible that due to tokenomics the today for one company this is affordable and or actually economical to deploy ai today or some decides to wait a little bit later while the let's say the models mature or the cost drops because there's two things happening at the same time Newer models going to enter at the same level of price points where they are today. Old models continue to become cheaper as the token price, execution price, inference costs for all those models are dropping. Some people are starting to deploy and actually actioning on this as they reach a certain entry point, and some people are waiting for newer models, as you're saying. Maturing, going through a maturity model, it's not really optional. In order to get access to the capabilities of the model, you have to go through this maturity. One way or the other, if you wanna tap into the power of the models, you will have to go from one to three. You're not going to get the benefits at level one. Newer models going to enter at the same level of price points where they are today. newer models going to enter at the same level of price points where they are today Old models continue to become cheaper as the token price, execution price, inference costs for all those models are dropping. old models continue to become cheaper as the token price execution price inference costs for all those models are dropping Some people are starting to deploy and actually actioning on this as they reach a certain entry point, and some people are waiting for newer models, as you're saying. some people are starting to deploy and actually actioning on this as they reach a certain entry point and some people are waiting for newer models as you're saying Maturing, going through a maturity model, it's not really optional. maturing going through a maturity model it's not really optional In order to get access to the capabilities of the model, you have to go through this maturity. in order to get access to the capabilities of the model you have to go through this maturity One way or the other, if you wanna tap into the power of the models, you will have to go from one to three. one way or the other if you wanna tap into the power of the models you will have to go from one to three You're not going to get the benefits at level one. you're not going to get the benefits at level one Actually, probably you're going to, as the models continue to evolve, you will be continuously even more disadvantaged by staying on level one. I don't know if it makes sense, but that's probably the right answer to this. Actually, probably you're going to, as the models continue to evolve, you will be continuously even more disadvantaged by staying on level one. actually probably you're going to as the models continue to evolve you will be continuously even more disadvantaged by staying on level one I don't know if it makes sense, but that's probably the right answer to this. i don't know if it makes sense but that's probably the right answer to this

Speaker 24: We have time for one more question here in the front, please. Jonathan. We have time for one more question here in the front, please. we have time for one more question here in the front please Jonathan. jonathan

Speaker 19: Jonathan Lee from Guggenheim. Thanks for hosting. FB, you mentioned, you know, different price points as it relates to models, but can you expand on EPAM's pricing strategy overall as it relates to how your new go-to-market and your AI-native approach impacts your pricing strategy going forward, especially as you balance, you know, agents versus perhaps higher cost team structures given talent scarcity? Jonathan Lee from Guggenheim. jonathan lee from guggenheim Thanks for hosting. thanks for hosting FB, you mentioned, you know, different price points as it relates to models, but can you expand on EPAM's pricing strategy overall as it relates to how your new go-to-market and your AI-native approach impacts your pricing strategy going forward, especially as you balance, you know, agents versus perhaps higher cost team structures given talent scarcity? fb you mentioned you know different price points as it relates to models but can you expand on epam's pricing strategy overall as it relates to how your new go-to-market and your ai-native approach impacts your pricing strategy going forward especially as you balance you know agents versus perhaps higher cost team structures given talent scarcity

Speaker 6: Jonathan, thank you much. It's a great question. I think as you saw from our results, we continues to be predominantly in a time and material model and we actually also communicated too that we were in Q4 we were successful getting rate increases from our clients, which actually indicates to us that the clients are receiving benefits of the more value which we deliver to them in the T&M model. But also I have to tell you that most of the times the tokens are paid by our clients because we are operating in the client's infrastructure due to security reason, due to data confidentiality. In that infrastructure, the clients are the ones who are deploying the models, and they're paying for the tokens. Jonathan, thank you much. jonathan thank you much It's a great question. it's a great question I think as you saw from our results, we continues to be predominantly in a time and material model and we actually also communicated too that we were in Q4 we were successful getting rate increases from our clients, which actually indicates to us that the clients are receiving benefits of the more value which we deliver to them in the T&M model. i think as you saw from our results we continues to be predominantly in a time and material model and we actually also communicated too that we were in q4 we were successful getting rate increases from our clients which actually indicates to us that the clients are receiving benefits of the more value which we deliver to them in the t&m model But also I have to tell you that most of the times the tokens are paid by our clients because we are operating in the client's infrastructure due to security reason, due to data confidentiality. but also i have to tell you that most of the times the tokens are paid by our clients because we are operating in the client's infrastructure due to security reason due to data confidentiality In that infrastructure, the clients are the ones who are deploying the models, and they're paying for the tokens. in that infrastructure the clients are the ones who are deploying the models and they're paying for the tokens Going forward basis, as we are migrating away or transitioning away from time and materials to more advanced, capabilities or more advanced contracting models, we will be seeing that it's going to be part of our, commercial model. We're going to factor in the price of the tokens into our, model itself on top of it or on, or in a more maybe on a transparent way. It's a work in progress how we're going to charge our clients the model, the tokens because as the tokens is the price is very volatile, so it's very difficult to figure out how to price it in at this point of time. We expect that once we are more in the fixed price or more advanced models, the cost of compute will be included in our price. Going forward basis, as we are migrating away or transitioning away from time and materials to more advanced, capabilities or more advanced contracting models, we will be seeing that it's going to be part of our, commercial model. going forward basis as we are migrating away or transitioning away from time and materials to more advanced capabilities or more advanced contracting models we will be seeing that it's going to be part of our commercial model We're going to factor in the price of the tokens into our, model itself on top of it or on, or in a more maybe on a transparent way. we're going to factor in the price of the tokens into our model itself on top of it or on or in a more maybe on a transparent way It's a work in progress how we're going to charge our clients the model, the tokens because as the tokens is the price is very volatile, so it's very difficult to figure out how to price it in at this point of time. it's a work in progress how we're going to charge our clients the model the tokens because as the tokens is the price is very volatile so it's very difficult to figure out how to price it in at this point of time We expect that once we are more in the fixed price or more advanced models, the cost of compute will be included in our price. we expect that once we are more in the fixed price or more advanced models the cost of compute will be included in our price Last but not least, I think one takeaway that our AI native projects and revenues are operating at higher profit levels compared to EPAM average. They're more profitable. Last but not least, I think one takeaway that our AI native projects and revenues are operating at higher profit levels compared to EPAM average. last but not least i think one takeaway that our ai native projects and revenues are operating at higher profit levels compared to epam average They're more profitable. they're more profitable

Speaker 24: That wraps the first Q&A session of the day. We're gonna take a break and reconvene here at the bottom of the hour, so 10:30 A.M. for those that are attending virtually. For those in the room, please enjoy some refreshments and drinks, and then we'll get back to our seats here. When we come up next, Arkadiy Dobkin, our Executive Chairman, will kick us off getting into our engineering DNA. Thank you very much. That wraps the first Q&A session of the day. that wraps the first q&a session of the day We're gonna take a break and reconvene here at the bottom of the hour, so 10:30 A.M. for those that are attending virtually. we're gonna take a break and reconvene here at the bottom of the hour so 10:30 a.m for those that are attending virtually For those in the room, please enjoy some refreshments and drinks, and then we'll get back to our seats here. for those in the room please enjoy some refreshments and drinks and then we'll get back to our seats here When we come up next, Arkadiy Dobkin, our Executive Chairman, will kick us off getting into our engineering DNA. when we come up next arkadiy dobkin our executive chairman will kick us off getting into our engineering dna Thank you very much. thank you very much

Speaker 35: People are probably familiar with the MIT report that boldly states 95% of companies are getting zero return on their AI investments. People are probably familiar with the MIT report that boldly states 95% of companies are getting zero return on their AI investments. people are probably familiar with the mit report that boldly states 95% of companies are getting zero return on their ai investments

Speaker 36: You don't have 10 years. You have 2. Three, maybe. You don't have 10 years. you don't have 10 years You have 2. you have 2 Three, maybe. three maybe

Speaker 37: I think AI will be transformational for the clinical experience in surgery. I think, it's going to improve patient outcomes. It's gonna reduce, burnout and burden on surgeons and nurses and respective teams in the hospitals. I think AI will be transformational for the clinical experience in surgery. i think ai will be transformational for the clinical experience in surgery I think, it's going to improve patient outcomes. i think it's going to improve patient outcomes It's gonna reduce, burnout and burden on surgeons and nurses and respective teams in the hospitals. it's gonna reduce burnout and burden on surgeons and nurses and respective teams in the hospitals

Speaker 38: At least 90% of the AI projects that are rolling out are failing within companies, and that's because it's an organization and a people adoption problem with AI. At least 90% of the AI projects that are rolling out are failing within companies, and that's because it's an organization and a people adoption problem with AI. at least 90% of the ai projects that are rolling out are failing within companies and that's because it's an organization and a people adoption problem with ai

Speaker 39: That we appear to be the anomalies, I think is really cool. We have a client base that is beating the trends. They're at the forefront of it. That we appear to be the anomalies, I think is really cool. that we appear to be the anomalies i think is really cool We have a client base that is beating the trends. we have a client base that is beating the trends They're at the forefront of it. they're at the forefront of it

Speaker 38: Taking something as nebulous as, and as confusing and sometimes scary as artificial intelligence and all the hype around it and turning that into, examples of really meaningful programs that EPAM is either in the middle of or fully executed, is the vision. Taking something as nebulous as, and as confusing and sometimes scary as artificial intelligence and all the hype around it and turning that into, examples of really meaningful programs that EPAM is either in the middle of or fully executed, is the vision. taking something as nebulous as and as confusing and sometimes scary as artificial intelligence and all the hype around it and turning that into examples of really meaningful programs that epam is either in the middle of or fully executed is the vision

Speaker 39: We really are starting to unlock useful, tangible results for our clients. These all go far, far beyond POC. These are scalable deployments of AI that are really delivering tangible business value for our clients today. We ingrain it in all of our projects. It's basically nature and, fundamental to what we do, trying to improve things and make things better. We really are starting to unlock useful, tangible results for our clients. we really are starting to unlock useful tangible results for our clients These all go far, far beyond POC. these all go far far beyond poc These are scalable deployments of AI that are really delivering tangible business value for our clients today. these are scalable deployments of ai that are really delivering tangible business value for our clients today We ingrain it in all of our projects. we ingrain it in all of our projects It's basically nature and, fundamental to what we do, trying to improve things and make things better. it's basically nature and fundamental to what we do trying to improve things and make things better

Speaker 38: EPAM is a fantastic partner for us actually on the sustainability journey and also building our global innovation strategy. EPAM is a fantastic partner for us actually on the sustainability journey and also building our global innovation strategy. epam is a fantastic partner for us actually on the sustainability journey and also building our global innovation strategy

Speaker 40: We've leveraged the EPAM partnership with their expertise. Putting our best foot forward has been a huge benefit. We've leveraged the EPAM partnership with their expertise. we've leveraged the epam partnership with their expertise Putting our best foot forward has been a huge benefit. putting our best foot forward has been a huge benefit

Speaker 41: EPAM have been a great delivery partner for us, both in terms of challenging us to making sure that we push the boundaries and making sure we're getting the basics right as well. EPAM have been a great delivery partner for us, both in terms of challenging us to making sure that we push the boundaries and making sure we're getting the basics right as well. epam have been a great delivery partner for us both in terms of challenging us to making sure that we push the boundaries and making sure we're getting the basics right as well

Speaker 39: What I think people get wrong about AI is that it is there to automate tasks and remove humans. It's gonna be much more of an exoskeleton, so it's gonna enhance people's capability, it's gonna make them faster, it's gonna make them smarter, it's gonna improve decision-making. What I think people get wrong about AI is that it is there to automate tasks and remove humans. what i think people get wrong about ai is that it is there to automate tasks and remove humans It's gonna be much more of an exoskeleton, so it's gonna enhance people's capability, it's gonna make them faster, it's gonna make them smarter, it's gonna improve decision-making. it's gonna be much more of an exoskeleton so it's gonna enhance people's capability it's gonna make them faster it's gonna make them smarter it's gonna improve decision-making

Speaker 38: Artificial intelligence in many ways is a complement to human intelligence and something that we should be looking for to actually propel enterprises and to propel sort of the enterprise of humanity forward. Artificial intelligence in many ways is a complement to human intelligence and something that we should be looking for to actually propel enterprises and to propel sort of the enterprise of humanity forward. artificial intelligence in many ways is a complement to human intelligence and something that we should be looking for to actually propel enterprises and to propel sort of the enterprise of humanity forward

Speaker 24: Eu já sei que nada será como antes amanhã. Mas eu sei também que você não tá falando a verdade, meu bem. Por favor, me deixa e mais, me dá um favor e sai da minha vida, porque eu sei que vou sofrer a cada despedida. Me dá um favor. Please make your way back to your seats. The program is about to begin. Eu já sei que nada será como antes amanhã. eu já sei que nada será como antes amanhã Mas eu sei também que você não tá falando a verdade, meu bem. mas eu sei também que você não tá falando a verdade meu bem Por favor, me deixa e mais, me dá um favor e sai da minha vida, porque eu sei que vou sofrer a cada despedida. por favor me deixa e mais me dá um favor e sai da minha vida porque eu sei que vou sofrer a cada despedida Me dá um favor. me dá um favor Please make your way back to your seats. please make your way back to your seats The program is about to begin. the program is about to begin

Speaker 5: Hello, everybody. Good to see many familiar faces here. I'm Arkadiy Dobkin, executive chairman and founder of the company. I've been here for a long time, and passed the CEO position to Balazs in September of last year, as you know. I think being here for a very long time and hearing the previous conversations and Q&A sessions where we actually try to answer very, very difficult questions and present the picture which conflicts not in very simple terms. We kind of engineer our presentations well, and I probably, based on the years, have a little bit more holistic and casual conversation today. There are three key messages which I think important. I would like to concentrate on this, that engineering excellence is still very. Sorry. Why Kevin was. Hello, everybody. hello everybody Good to see many familiar faces here. good to see many familiar faces here I'm Arkadiy Dobkin, executive chairman and founder of the company. i'm arkadiy dobkin executive chairman and founder of the company I've been here for a long time, and passed the CEO position to Balazs in September of last year, as you know. i've been here for a long time and passed the ceo position to balazs in september of last year as you know I think being here for a very long time and hearing the previous conversations and Q&A sessions where we actually try to answer very, very difficult questions and present the picture which conflicts not in very simple terms. i think being here for a very long time and hearing the previous conversations and q&a sessions where we actually try to answer very very difficult questions and present the picture which conflicts not in very simple terms We kind of engineer our presentations well, and I probably, based on the years, have a little bit more holistic and casual conversation today. we kind of engineer our presentations well and i probably based on the years have a little bit more holistic and casual conversation today There are three key messages which I think important. there are three key messages which i think important I would like to concentrate on this, that engineering excellence is still very. i would like to concentrate on this that engineering excellence is still very Sorry. sorry Why Kevin was. why kevin was Engineering excellence is critical differentiator, and in the AI age, it's even more important to cut through entire implementation cycle. I think history matters, and similar like in previous waves, I don't think it's going to be revolution. It's going to be evolution for multiple reasons, and I think history is important to remember. I think similar like in the past, the human talent will be the critical differentiator. Everything else will become eventually equalized and become more commodity. Actually the people who deliver in the last mile will be critical. With this, I would like to, for a couple of minutes, go back to the history and explain, at least for some new people in the audience, that from the very beginning, EPAM was slightly different than other major players on IT services market. Engineering excellence is critical differentiator, and in the AI age, it's even more important to cut through entire implementation cycle. engineering excellence is critical differentiator and in the ai age it's even more important to cut through entire implementation cycle I think history matters, and similar like in previous waves, I don't think it's going to be revolution. i think history matters and similar like in previous waves i don't think it's going to be revolution It's going to be evolution for multiple reasons, and I think history is important to remember. it's going to be evolution for multiple reasons and i think history is important to remember I think similar like in the past, the human talent will be the critical differentiator. i think similar like in the past the human talent will be the critical differentiator Everything else will become eventually equalized and become more commodity. everything else will become eventually equalized and become more commodity Actually the people who deliver in the last mile will be critical. actually the people who deliver in the last mile will be critical With this, I would like to, for a couple of minutes, go back to the history and explain, at least for some new people in the audience, that from the very beginning, EPAM was slightly different than other major players on IT services market. with this i would like to for a couple of minutes go back to the history and explain at least for some new people in the audience that from the very beginning epam was slightly different than other major players on it services market Our first clients were software companies, and for the first 10 years, 100% of our services were focusing on building products for software companies. Very, very different business. The second 10 years, we started to work with digital natives, Google's, Expedia's, Epic Games', games of the world, and actually helping them to scale. At the same time, you understand that this 20 years of our first years of existence actually established very different DNA, very different processes, very different talent selection than majority of the industry. It's important, and it's become important after our IPO when we grew very, very fast, when we were able to address the demand of completely different skills. I am using the same slide, which is already in Balazs presentation because the question which you asking and we asking ourself, is it still important? Our first clients were software companies, and for the first 10 years, 100% of our services were focusing on building products for software companies. our first clients were software companies and for the first 10 years 100% of our services were focusing on building products for software companies Very, very different business. very very different business The second 10 years, we started to work with digital natives, Google's, Expedia's, Epic Games', games of the world, and actually helping them to scale. the second 10 years we started to work with digital natives google's expedia's epic games' games of the world and actually helping them to scale At the same time, you understand that this 20 years of our first years of existence actually established very different DNA, very different processes, very different talent selection than majority of the industry. at the same time you understand that this 20 years of our first years of existence actually established very different dna very different processes very different talent selection than majority of the industry It's important, and it's become important after our IPO when we grew very, very fast, when we were able to address the demand of completely different skills. it's important and it's become important after our ipo when we grew very very fast when we were able to address the demand of completely different skills I am using the same slide, which is already in Balazs presentation because the question which you asking and we asking ourself, is it still important? i am using the same slide which is already in balazs presentation because the question which you asking and we asking ourself is it still important Is this engineering DNA still going to be differentiator with all this noise and rumors and credible people talking around us how code is over and maybe code is over, but what about engineering? Maybe engineering is over and what the next model will bring and all of this. With this, I would like to add opinion of one more expert, and I'm not going to read the slide, but please read it. Or even in short, the author said this: "Programmer is about to share the fate of the Dodo bird. By the end of this decade, I foresee massive unemployment among the ranks of programmer, system analyst, and software engineers." It was published in this book in 1992. It wasn't published by somebody. It was published by Edward Yourdon, who was a father of structuring programmer and critical person in creating object-oriented programming. Is this engineering DNA still going to be differentiator with all this noise and rumors and credible people talking around us how code is over and maybe code is over, but what about engineering? is this engineering dna still going to be differentiator with all this noise and rumors and credible people talking around us how code is over and maybe code is over but what about engineering Maybe engineering is over and what the next model will bring and all of this. maybe engineering is over and what the next model will bring and all of this With this, I would like to add opinion of one more expert, and I'm not going to read the slide, but please read it. with this i would like to add opinion of one more expert and i'm not going to read the slide but please read it Or even in short, the author said this: "Programmer is about to share the fate of the Dodo bird. or even in short the author said this "programmer is about to share the fate of the dodo bird By the end of this decade, I foresee massive unemployment among the ranks of programmer, system analyst, and software engineers." It was published in this book in 1992. by the end of this decade i foresee massive unemployment among the ranks of programmer system analyst and software engineers." it was published in this book in 1992 It wasn't published by somebody. it wasn't published by somebody It was published by Edward Yourdon, who was a father of structuring programmer and critical person in creating object-oriented programming. it was published by edward yourdon who was a father of structuring programmer and critical person in creating object-oriented programming He was a visionary and one of the top 10 computer scientists of his generation. Why I'm saying visionary? Because this book was published in 1992. His thesis was that offshoring and new programming methodologies will kill American programmers. Think about 1992. The whole offshoring in the market was $100 million from about $100 billion-$200 billion global IT. He was brilliant. Three years later, four years later, he published another book called Rise and Resurrection of the American Programmer because he admitted that he hugely underestimated entrepreneurial drive, Silicon Valley innovation, growth of economy thanks to internet, and one more point, complexity of the enterprise. He hugely underestimated that, and he was wrong in his first book. This bring us to actually the EPAM life cycle, the history, the ways from foundation to going through the crises. He was a visionary and one of the top 10 computer scientists of his generation. he was a visionary and one of the top 10 computer scientists of his generation Why I'm saying visionary? why i'm saying visionary Because this book was published in 1992. because this book was published in 1992 His thesis was that offshoring and new programming methodologies will kill American programmers. his thesis was that offshoring and new programming methodologies will kill american programmers Think about 1992. think about 1992 The whole offshoring in the market was $100 million from about $100 billion-$200 billion global IT. the whole offshoring in the market was $100 million from about $100 billion-$200 billion global it He was brilliant. he was brilliant Three years later, four years later, he published another book called Rise and Resurrection of the American Programmer because he admitted that he hugely underestimated entrepreneurial drive, Silicon Valley innovation, growth of economy thanks to internet, and one more point, complexity of the enterprise. three years later four years later he published another book called rise and resurrection of the american programmer because he admitted that he hugely underestimated entrepreneurial drive silicon valley innovation growth of economy thanks to internet and one more point complexity of the enterprise He hugely underestimated that, and he was wrong in his first book. he hugely underestimated that and he was wrong in his first book This bring us to actually the EPAM life cycle, the history, the ways from foundation to going through the crises. this bring us to actually the epam life cycle the history the ways from foundation to going through the crises We started in 1993, actually, at some level inspired by his book about offshoring. We ran to the internet era. You know what? At this point, the skills which have to deliver this new type of applications didn't exist. You cannot go to the market and buy. Each of this internet, including actually created the hype, the programmers, C++, C or C++ like real people don't need anymore. HTML coders will do it. Then it was disappearing because each time complexity was underestimated. We came to era of cloud, mobile, and data, and same stuff. We as an engineering firm, we're starting to build our own platforms. It's been mentioned TelescopeAI, we will talk a little bit more about it. We started in 1993, actually, at some level inspired by his book about offshoring. we started in 1993 actually at some level inspired by his book about offshoring We ran to the internet era. we ran to the internet era You know what? you know what At this point, the skills which have to deliver this new type of applications didn't exist. at this point the skills which have to deliver this new type of applications didn't exist You cannot go to the market and buy. you cannot go to the market and buy Each of this internet, including actually created the hype, the programmers, C++, C or C++ like real people don't need anymore. each of this internet including actually created the hype the programmers c++ c or c++ like real people don't need anymore HTML coders will do it. html coders will do it Then it was disappearing because each time complexity was underestimated. then it was disappearing because each time complexity was underestimated We came to era of cloud, mobile, and data, and same stuff. we came to era of cloud mobile and data and same stuff We as an engineering firm, we're starting to build our own platforms. we as an engineering firm we're starting to build our own platforms It's been mentioned TelescopeAI, we will talk a little bit more about it. it's been mentioned telescopeai we will talk a little bit more about it We also engineer not only digital platform, we engineer our educational learning platform as well, because we cannot find these people, we have to find the right candidates and develop them. That's what we did during this second era better than anybody else. That's why we were growing. This is where was impossible to predict what type of new applications going to happen. Think about it. We're talking about AI impact on existing type of applications, and that's what underestimating coming from, because the main change going to be in the future, and we don't know yet what it is. We also engineer not only digital platform, we engineer our educational learning platform as well, because we cannot find these people, we have to find the right candidates and develop them. we also engineer not only digital platform we engineer our educational learning platform as well because we cannot find these people we have to find the right candidates and develop them That's what we did during this second era better than anybody else. that's what we did during this second era better than anybody else That's why we were growing. that's why we were growing This is where was impossible to predict what type of new applications going to happen. this is where was impossible to predict what type of new applications going to happen Think about it. think about it We're talking about AI impact on existing type of applications, and that's what underestimating coming from, because the main change going to be in the future, and we don't know yet what it is. we're talking about ai impact on existing type of applications and that's what underestimating coming from because the main change going to be in the future and we don't know yet what it is Now we're in AI era, and that's what we were covering before me, and the pattern again across all of this was that every productivity, whether from 4GL to object-oriented to open source low-code, promised to reduce builders' demand, and in practice, each time the lower cost went, the more market expanded. More opportunity, more cheaper were done new, and this new were growing like a snowball. That's why if you think about in addition to everything else, what's happening with regular productivity, which we kind of focused in the first part, entrepreneurial drive of people, innovation levels of something which you have no idea about it today, potential economy growth with AI and making everything cheaper in intelligence and enterprise complexity, which I don't think I need to explain. Even with the comment before that some of companies even didn't buy the tools. Now we're in AI era, and that's what we were covering before me, and the pattern again across all of this was that every productivity, whether from 4GL to object-oriented to open source low-code, promised to reduce builders' demand, and in practice, each time the lower cost went, the more market expanded. now we're in ai era and that's what we were covering before me and the pattern again across all of this was that every productivity whether from 4gl to object-oriented to open source low-code promised to reduce builders' demand and in practice each time the lower cost went the more market expanded More opportunity, more cheaper were done new, and this new were growing like a snowball. more opportunity more cheaper were done new and this new were growing like a snowball That's why if you think about in addition to everything else, what's happening with regular productivity, which we kind of focused in the first part, entrepreneurial drive of people, innovation levels of something which you have no idea about it today, potential economy growth with AI and making everything cheaper in intelligence and enterprise complexity, which I don't think I need to explain. that's why if you think about in addition to everything else what's happening with regular productivity which we kind of focused in the first part entrepreneurial drive of people innovation levels of something which you have no idea about it today potential economy growth with ai and making everything cheaper in intelligence and enterprise complexity which i don't think i need to explain Even with the comment before that some of companies even didn't buy the tools. even with the comment before that some of companies even didn't buy the tools The silos of knowledge so huge in corporations, you, working there, you know. AI not going to bring any benefit unless it's all uncovered together. With this, in the AI era, it's going to be actually growing demand. I'm pretty sure about it. Not theoretically for very real. We enter the market when traditional software could never afford to serve before. The last mile become very critical build differentiation. Everything else will be equalized. We're going to address levels of complexity we have no idea about it today. Similar like think each time 10 years back. Think from AWS to Amazon bookstore. Can we imagine all of this happening? I think the shift of the bottleneck going to be up and up, and the last 80%-20%, which usually taking 80% of the big engagement because of complexity, they will move even to higher average. The silos of knowledge so huge in corporations, you, working there, you know. the silos of knowledge so huge in corporations you working there you know AI not going to bring any benefit unless it's all uncovered together. ai not going to bring any benefit unless it's all uncovered together With this, in the AI era, it's going to be actually growing demand. with this in the ai era it's going to be actually growing demand I'm pretty sure about it. i'm pretty sure about it Not theoretically for very real. not theoretically for very real We enter the market when traditional software could never afford to serve before. we enter the market when traditional software could never afford to serve before The last mile become very critical build differentiation. the last mile become very critical build differentiation Everything else will be equalized. everything else will be equalized We're going to address levels of complexity we have no idea about it today. we're going to address levels of complexity we have no idea about it today Similar like think each time 10 years back. similar like think each time 10 years back Think from AWS to Amazon bookstore. think from aws to amazon bookstore Can we imagine all of this happening? can we imagine all of this happening I think the shift of the bottleneck going to be up and up, and the last 80%-20% , which usually taking 80% of the big engagement because of complexity, they will move even to higher average. i think the shift of the bottleneck going to be up and up and the last 80%-20% which usually taking 80% of the big engagement because of complexity they will move even to higher average The 80% was relatively easy. Yes, it would be much more easier to do. I think at this situation, the people who delivering this last mile, leading this last mile, which would be very, very scalable, it's a key differentiation, and these people who has to work in ambiguity, in unknown, think very quickly because AI making everything older very, very fast. I think bringing another current authority, Boris Cherny, he's like probably you saw his podcast. He was talking about exactly importance of engineers, and this is what Dima was talking about it, this full stack agentic engineer who can coordinate. People who can orchestrate. If you think that it's very new thing, that it's a mistake. I think that's exactly EPAM was benefiting from this type of people in complexity during the previous decade. The 80% was relatively easy. the 80% was relatively easy Yes, it would be much more easier to do. yes it would be much more easier to do I think at this situation, the people who delivering this last mile, leading this last mile, which would be very, very scalable, it's a key differentiation, and these people who has to work in ambiguity, in unknown, think very quickly because AI making everything older very, very fast. i think at this situation the people who delivering this last mile leading this last mile which would be very very scalable it's a key differentiation and these people who has to work in ambiguity in unknown think very quickly because ai making everything older very very fast I think bringing another current authority, Boris Cherny, he's like probably you saw his podcast. i think bringing another current authority boris cherny he's like probably you saw his podcast He was talking about exactly importance of engineers, and this is what Dima was talking about it, this full stack agentic engineer who can coordinate. he was talking about exactly importance of engineers and this is what dima was talking about it this full stack agentic engineer who can coordinate People who can orchestrate. people who can orchestrate If you think that it's very new thing, that it's a mistake. if you think that it's very new thing that it's a mistake I think that's exactly EPAM was benefiting from this type of people in complexity during the previous decade. i think that's exactly epam was benefiting from this type of people in complexity during the previous decade This is how we differentiate ourselves in the past. The point was that with talent we built, sometimes these type of people were not even in enough demand. We were putting them on some coding positions. We understand with our insight to the systems and to our educational learning process, which we're going to talk about in a minute, how to identify them, how to develop them, and how to scale them historically for the last decades. Key takeaways. We're probably really underestimating the scale of AI-driven market expansion and the complexity of enterprise. The second, engineering matters, and Anthropic people saying this as well. Coding simple, engineering becoming much more sophisticated. Think about it like new terms which come in like almost each couple months. Prompt engineering, okay, this is legacy. Context engineering, intent engineering, I don't know what will be tomorrow. This is how we differentiate ourselves in the past. this is how we differentiate ourselves in the past The point was that with talent we built, sometimes these type of people were not even in enough demand. the point was that with talent we built sometimes these type of people were not even in enough demand We were putting them on some coding positions. we were putting them on some coding positions We understand with our insight to the systems and to our educational learning process, which we're going to talk about in a minute, how to identify them, how to develop them, and how to scale them historically for the last decades. we understand with our insight to the systems and to our educational learning process which we're going to talk about in a minute how to identify them how to develop them and how to scale them historically for the last decades Key takeaways. key takeaways We're probably really underestimating the scale of AI-driven market expansion and the complexity of enterprise. we're probably really underestimating the scale of ai-driven market expansion and the complexity of enterprise The second, engineering matters, and Anthropic people saying this as well. the second engineering matters and anthropic people saying this as well Coding simple, engineering becoming much more sophisticated. coding simple engineering becoming much more sophisticated Think about it like new terms which come in like almost each couple months. think about it like new terms which come in like almost each couple months Prompt engineering, okay, this is legacy. prompt engineering okay this is legacy Context engineering, intent engineering, I don't know what will be tomorrow. context engineering intent engineering i don't know what will be tomorrow Right talent, and this was 30 years of our focus. By the way, Dima, who was presenting here, he was graduating from computer science, but he went through our educational six-month boot camp before he started to work at EPAM. That was happening 20 years ago, and this is what's happening today. Thank you, and I would like to invite Sandra, our Chief Learning Scientist, and Alexei, who is the Head of Engineering Excellence, actually to bring much more details on what I was sharing with you. Right talent, and this was 30 years of our focus. right talent and this was 30 years of our focus By the way, Dima, who was presenting here, he was graduating from computer science, but he went through our educational six-month boot camp before he started to work at EPAM. That was happening 20 years ago, and this is what's happening today. by the way dima who was presenting here he was graduating from computer science but he went through our educational six-month boot camp before he started to work at epam. that was happening 20 years ago and this is what's happening today Thank you, and I would like to invite Sandra, our Chief Learning Scientist, and Alexei, who is the Head of Engineering Excellence, actually to bring much more details on what I was sharing with you. thank you and i would like to invite sandra our chief learning scientist and alexei who is the head of engineering excellence actually to bring much more details on what i was sharing with you

Speaker 3: All right. Good morning. My name is Alexei Didyk. I'm Head of Engineering Excellence AI. All right. all right Good morning. good morning My name is Alexei Didyk. my name is alexei didyk I'm Head of Engineering Excellence AI. i'm head of engineering excellence ai

Speaker 30: I'm Sandra Loughlin. I am EPAM's Chief Learning Scientist. I'm Sandra Loughlin. i'm sandra loughlin I am EPAM's Chief Learning Scientist. i am epam's chief learning scientist

Speaker 3: Arkadiy just showed us that we need the right talent. Dmitry and Adam gave us a glance of a full stack agentic engineer, and it was even a question from the audience, who are those people? Let's take a look. A full stack agentic engineer is not just a new role which build from scratch for AI era. It's a evolution. It's built on a foundation of narrow specialists available in the industry. In EPAM, narrow specialists, they're also already better because of our engineering DNA, culture, and excellence. Now we need to extend this foundation with a full stack development, ownership of application layers across all technologies. We need to deepen it with a understanding of AI tooling and also understanding of AI-native workflows, capability to orchestrate agent fleets across all stages of development. How we can even approach this new talent profile? Arkadiy just showed us that we need the right talent. arkadiy just showed us that we need the right talent Dmitry and Adam gave us a glance of a full stack agentic engineer, and it was even a question from the audience, who are those people? dmitry and adam gave us a glance of a full stack agentic engineer and it was even a question from the audience who are those people Let's take a look. let's take a look A full stack agentic engineer is not just a new role which build from scratch for AI era. a full stack agentic engineer is not just a new role which build from scratch for ai era It's a evolution. it's a evolution It's built on a foundation of narrow specialists available in the industry. it's built on a foundation of narrow specialists available in the industry In EPAM, narrow specialists, they're also already better because of our engineering DNA, culture, and excellence. in epam narrow specialists they're also already better because of our engineering dna culture and excellence Now we need to extend this foundation with a full stack development, ownership of application layers across all technologies. now we need to extend this foundation with a full stack development ownership of application layers across all technologies We need to deepen it with a understanding of AI tooling and also understanding of AI-native workflows, capability to orchestrate agent fleets across all stages of development. we need to deepen it with a understanding of ai tooling and also understanding of ai-native workflows capability to orchestrate agent fleets across all stages of development How we can even approach this new talent profile? how we can even approach this new talent profile How we can build it? We are doing it by breaking it into skills. Skills which are becoming less prominent and important, skills which still need to stay because I still might have, and the skills which are emerging and rising because they're becoming a new must-have. How we build those talents. To build those talents, we have our educational program with universal coverage, and we build this program using our own proprietary courses. We do not want just to use materials from the market because we believe that external knowledge need to be processed and passed through the lenses of EPAM experience, our experience to deliver AI-native work. How we can build it? how we can build it We are doing it by breaking it into skills. we are doing it by breaking it into skills Skills which are becoming less prominent and important, skills which still need to stay because I still might have, and the skills which are emerging and rising because they're becoming a new must-have. skills which are becoming less prominent and important skills which still need to stay because i still might have and the skills which are emerging and rising because they're becoming a new must-have How we build those talents. how we build those talents To build those talents, we have our educational program with universal coverage, and we build this program using our own proprietary courses. to build those talents we have our educational program with universal coverage and we build this program using our own proprietary courses We do not want just to use materials from the market because we believe that external knowledge need to be processed and passed through the lenses of EPAM experience, our experience to deliver AI-native work. we do not want just to use materials from the market because we believe that external knowledge need to be processed and passed through the lenses of epam experience our experience to deliver ai-native work We combine it with a formal education and informal education, running a global AI conference last year, thousands of people, 45 countries, because it's important to build horizontal connection with people, between people, so they can exchange knowledge, learn from someone next door. We run master classes together with our partners from Amazon and Microsoft. It's a very good program, but is it enough? We combine it with a formal education and informal education, running a global AI conference last year, thousands of people, 45 countries, because it's important to build horizontal connection with people, between people, so they can exchange knowledge, learn from someone next door. we combine it with a formal education and informal education running a global ai conference last year thousands of people 45 countries because it's important to build horizontal connection with people between people so they can exchange knowledge learn from someone next door We run master classes together with our partners from Amazon and Microsoft. we run master classes together with our partners from amazon and microsoft It's a very good program, but is it enough? it's a very good program but is it enough

Speaker 30: If that seemed common to you, it is. Percent of employees who've gone through courses, who's clicked through what, how many classes do you have? Those metrics are table stakes. Worse, they're illusions of competence. Training people is not a strategy, and it's certainly not a differentiation. Leading in the AI services market requires going far beyond those basics. Building the AI-native talent that you've been hearing about today is actually a three-pronged challenge. It starts with identifying the skills that are in demand today and, critically, the ones that will be needed tomorrow. Exactly the kind of skills that you heard about this morning from Dima and Adam and Arkadiy. Development really isn't about training. People can train and learn nothing, and most people learn from informal things like reflection and practice and getting feedback. For development, there are two key things to learn about. If that seemed common to you, it is. if that seemed common to you it is Percent of employees who've gone through courses, who's clicked through what, how many classes do you have? percent of employees who've gone through courses who's clicked through what how many classes do you have Those metrics are table stakes. those metrics are table stakes Worse, they're illusions of competence. worse they're illusions of competence Training people is not a strategy, and it's certainly not a differentiation. training people is not a strategy and it's certainly not a differentiation Leading in the AI services market requires going far beyond those basics. leading in the ai services market requires going far beyond those basics Building the AI-native talent that you've been hearing about today is actually a three-pronged challenge. building the ai-native talent that you've been hearing about today is actually a three-pronged challenge It starts with identifying the skills that are in demand today and, critically, the ones that will be needed tomorrow. it starts with identifying the skills that are in demand today and critically the ones that will be needed tomorrow Exactly the kind of skills that you heard about this morning from Dima and Adam and Arkadiy. exactly the kind of skills that you heard about this morning from dima and adam and arkadiy Development really isn't about training. development really isn't about training People can train and learn nothing, and most people learn from informal things like reflection and practice and getting feedback. people can train and learn nothing and most people learn from informal things like reflection and practice and getting feedback For development, there are two key things to learn about. for development there are two key things to learn about One is motivation. Can organizations drive their people to learn even when it's hard or not fun? The second is validating the skills. If you can't use those skills in production, it doesn't matter. The most critical metric for a professional services organization is actually deployment. Can you put the right skills and the right combinations on the right client projects to create value? This three-pronged challenge fundamentally shifts the metrics that matter for talent development. Instead of focusing on number of people trained, the companies that grow people and those that invest in them should be thinking about different metrics altogether. How quickly can you sense the right skills? How fast and how thoroughly are people upskilling and demonstrating that they're using those skills in practice? Critically, how quickly are you staffing the right people to the right client projects? One is motivation. one is motivation Can organizations drive their people to learn even when it's hard or not fun? can organizations drive their people to learn even when it's hard or not fun The second is validating the skills. the second is validating the skills If you can't use those skills in production, it doesn't matter. if you can't use those skills in production it doesn't matter The most critical metric for a professional services organization is actually deployment. the most critical metric for a professional services organization is actually deployment Can you put the right skills and the right combinations on the right client projects to create value? can you put the right skills and the right combinations on the right client projects to create value This three-pronged challenge fundamentally shifts the metrics that matter for talent development. this three-pronged challenge fundamentally shifts the metrics that matter for talent development Instead of focusing on number of people trained, the companies that grow people and those that invest in them should be thinking about different metrics altogether. instead of focusing on number of people trained the companies that grow people and those that invest in them should be thinking about different metrics altogether How quickly can you sense the right skills? how quickly can you sense the right skills How fast and how thoroughly are people upskilling and demonstrating that they're using those skills in practice? how fast and how thoroughly are people upskilling and demonstrating that they're using those skills in practice Critically, how quickly are you staffing the right people to the right client projects? critically how quickly are you staffing the right people to the right client projects In this era, the future will be made by those people who focus on those metrics. You're not gonna be surprised to hear that is who we are. For years, you have heard about TelescopeAI, EPAM's proprietary 30-year, homegrown, in-the-making system that is focused on people and the backbone of our business. Today, you're learning why we keep talking about it, and that's because TelescopeAI was purpose-built to do exactly these three things. In a world where organizations know more about the chairs in their buildings than the skills of the people who sit in them, EPAM has built our business to know exactly what we need, who we have, and where best to put them. For a company whose business is people, that knowledge is competitive advantage. Before Alexei shows you the metrics that we track, please know that some of these numbers are operational and proprietary. In this era, the future will be made by those people who focus on those metrics. in this era the future will be made by those people who focus on those metrics You're not gonna be surprised to hear that is who we are. you're not gonna be surprised to hear that is who we are For years, you have heard about TelescopeAI, EPAM's proprietary 30-year, homegrown, in-the-making system that is focused on people and the backbone of our business. for years you have heard about telescopeai epam's proprietary 30-year homegrown in-the-making system that is focused on people and the backbone of our business Today, you're learning why we keep talking about it, and that's because TelescopeAI was purpose-built to do exactly these three things. today you're learning why we keep talking about it and that's because telescopeai was purpose-built to do exactly these three things In a world where organizations know more about the chairs in their buildings than the skills of the people who sit in them, EPAM has built our business to know exactly what we need, who we have, and where best to put them. in a world where organizations know more about the chairs in their buildings than the skills of the people who sit in them epam has built our business to know exactly what we need who we have and where best to put them For a company whose business is people, that knowledge is competitive advantage. for a company whose business is people that knowledge is competitive advantage Before Alexei shows you the metrics that we track, please know that some of these numbers are operational and proprietary. before alexei shows you the metrics that we track please know that some of these numbers are operational and proprietary That's why you're not gonna see hard numbers for everything. Most importantly, you can't interpret these numbers without a context, and the industry is just not there yet. They're not tracking the same numbers that we are. We believe that they will get there. We think it is inevitable, and we're excited about that, the day when they do. Until then, we're gonna offer you a glimpse into how we treat talent as a business asset. That's why you're not gonna see hard numbers for everything. that's why you're not gonna see hard numbers for everything Most importantly, you can't interpret these numbers without a context, and the industry is just not there yet. most importantly you can't interpret these numbers without a context and the industry is just not there yet They're not tracking the same numbers that we are. they're not tracking the same numbers that we are We believe that they will get there. we believe that they will get there We think it is inevitable, and we're excited about that, the day when they do. we think it is inevitable and we're excited about that the day when they do Until then, we're gonna offer you a glimpse into how we treat talent as a business asset. until then we're gonna offer you a glimpse into how we treat talent as a business asset

Speaker 3: We have three functions, sense, develop and deploy. Sensing starts from market and industry. Industry first. Our practice leads carefully process all information coming from the industry on what is gonna happen in the next months and years. We do not just listen. We process and convert this information into skills. Skills which are retiring, retaining or rising because it drives the development of our learning programs. The same skills are used to understand demand on the market and predict demand on the market because we know how much new positions our clients need with AI-ready skills. I should say that this demand is quickly accelerating. It's not enough just to sense industry and the market. We need to sense our people to understand the why, how we can provide them to our clients. We have three functions, sense, develop and deploy. we have three functions sense develop and deploy Sensing starts from market and industry. sensing starts from market and industry Industry first. industry first Our practice leads carefully process all information coming from the industry on what is gonna happen in the next months and years. our practice leads carefully process all information coming from the industry on what is gonna happen in the next months and years We do not just listen. we do not just listen We process and convert this information into skills. we process and convert this information into skills Skills which are retiring, retaining or rising because it drives the development of our learning programs. skills which are retiring retaining or rising because it drives the development of our learning programs The same skills are used to understand demand on the market and predict demand on the market because we know how much new positions our clients need with AI-ready skills. the same skills are used to understand demand on the market and predict demand on the market because we know how much new positions our clients need with ai-ready skills I should say that this demand is quickly accelerating. i should say that this demand is quickly accelerating It's not enough just to sense industry and the market. it's not enough just to sense industry and the market We need to sense our people to understand the why, how we can provide them to our clients. we need to sense our people to understand the why how we can provide them to our clients This sensing is definitely not only about how many training modules they completed. This sensing is about the way how they converted this knowledge into a real work experience and build real skill. We combine evidence from different sources, from the complexity of delivery of real work they've done, from reviews and assessments, how quickly they learn, endorsements from their peers, and it all together creates a universal standard applicable across all our global workforce, across all our countries. I should say that we are sensing that we have enough AI-ready engineers to cover all our client needs. Now we need to deploy. We don't want to deploy people just based on availability. We want to deploy people based on their verified mastery, based on our ability to provide fit-for-purpose engineers to our client. This sensing is definitely not only about how many training modules they completed. this sensing is definitely not only about how many training modules they completed This sensing is about the way how they converted this knowledge into a real work experience and build real skill. this sensing is about the way how they converted this knowledge into a real work experience and build real skill We combine evidence from different sources, from the complexity of delivery of real work they've done, from reviews and assessments, how quickly they learn, endorsements from their peers, and it all together creates a universal standard applicable across all our global workforce, across all our countries. we combine evidence from different sources from the complexity of delivery of real work they've done from reviews and assessments how quickly they learn endorsements from their peers and it all together creates a universal standard applicable across all our global workforce across all our countries I should say that we are sensing that we have enough AI-ready engineers to cover all our client needs. i should say that we are sensing that we have enough ai-ready engineers to cover all our client needs Now we need to deploy. now we need to deploy We don't want to deploy people just based on availability. we don't want to deploy people just based on availability We want to deploy people based on their verified mastery, based on our ability to provide fit-for-purpose engineers to our client. we want to deploy people based on their verified mastery based on our ability to provide fit-for-purpose engineers to our client That's why our TelescopeAI and proprietary AI-driven matching model uses 25 different attributes to find the right people with the right skill for the right project of our clients. Results are evident. Roughly 80% of positions with AI skills at this moment are staffed within seven days, and the rest doesn't take much longer. It's about speed, because you can staff quickly, but is it a quality? Quality is here. Our NPS, in comparison from 2024 to 2025, grew by +4% and taking into account that our NPS is already above industry average. That's why our TelescopeAI and proprietary AI-driven matching model uses 25 different attributes to find the right people with the right skill for the right project of our clients. that's why our telescopeai and proprietary ai-driven matching model uses 25 different attributes to find the right people with the right skill for the right project of our clients Results are evident. results are evident Roughly 80% of positions with AI skills at this moment are staffed within seven days, and the rest doesn't take much longer. roughly 80% of positions with ai skills at this moment are staffed within seven days and the rest doesn't take much longer It's about speed, because you can staff quickly, but is it a quality? it's about speed because you can staff quickly but is it a quality Quality is here. quality is here Our NPS, in comparison from 2024 to 2025, grew by +4% and taking into account that our NPS is already above industry average. our nps in comparison from 2024 to 2025 grew by +4% and taking into account that our nps is already above industry average

Speaker 30: The fact that we have hundreds of university partners is good, but the way that we use them is actually what matters. Instead of relying on faculty to keep pace with AI or hope that they listen to us and change their courses, we learned long ago to engage directly with students like Alexei, like Dima, using our own instructors and our own proprietary coursework, the same coursework that we use with our people inside. This means that students in our pipeline are trained on our evolving definition of AI talent, and they're tuned for local client demand. Because we've invested in them and because we have built relationships, EPAM gets to snap up the best talent before anyone else. This model is not new for AI. It's how we've operated forever, and it's not something special that happens in one geography. The fact that we have hundreds of university partners is good, but the way that we use them is actually what matters. the fact that we have hundreds of university partners is good but the way that we use them is actually what matters Instead of relying on faculty to keep pace with AI or hope that they listen to us and change their courses, we learned long ago to engage directly with students like Alexei, like Dima, using our own instructors and our own proprietary coursework, the same coursework that we use with our people inside. instead of relying on faculty to keep pace with ai or hope that they listen to us and change their courses we learned long ago to engage directly with students like alexei like dima using our own instructors and our own proprietary coursework the same coursework that we use with our people inside This means that students in our pipeline are trained on our evolving definition of AI talent, and they're tuned for local client demand. this means that students in our pipeline are trained on our evolving definition of ai talent and they're tuned for local client demand Because we've invested in them and because we have built relationships, EPAM gets to snap up the best talent before anyone else. because we've invested in them and because we have built relationships epam gets to snap up the best talent before anyone else This model is not new for AI. this model is not new for ai It's how we've operated forever, and it's not something special that happens in one geography. it's how we've operated forever and it's not something special that happens in one geography We built this model in Eastern Europe and then scaled it to all of our major delivery centers around the world, and that's why, as you will hear from Larry and Vic, we can have a standard very high for engineering talent anywhere we go in the world. Four years ago, I stood here and said, "Young EPAMers can't be hired, they can only be built." That has not changed, but the value to our business has. In a world where AI native juniors aren't available anywhere on the market, EPAM has a global pipeline prepared for local client demand on day one. We built this model in Eastern Europe and then scaled it to all of our major delivery centers around the world, and that's why, as you will hear from Larry and Vic, we can have a standard very high for engineering talent anywhere we go in the world. we built this model in eastern europe and then scaled it to all of our major delivery centers around the world and that's why as you will hear from larry and vic we can have a standard very high for engineering talent anywhere we go in the world Four years ago, I stood here and said, "Young EPAMers can't be hired, they can only be built." That has not changed, but the value to our business has. four years ago i stood here and said "young epamers can't be hired they can only be built." that has not changed but the value to our business has In a world where AI native juniors aren't available anywhere on the market, EPAM has a global pipeline prepared for local client demand on day one. in a world where ai native juniors aren't available anywhere on the market epam has a global pipeline prepared for local client demand on day one

Speaker 3: Results are evident. We have an engine and it's running. We are sensing the market in an industry which allows us to predict what's gonna happen next and how many people we need. It helps us to build the supply depths through our learning programs, combining formal and informal education, and then verifies the skills to be sure through the real delivery, through the production. We are able to deploy our people fit for purpose, right skills, right people for the right project. We can do it quickly and keeping quality. Deploy function goes back to the sense, and that's the way how the feedback loop completes. That's how the whole engine is working. We can not only today create several full stack agentic engineers, so many of them, we can do it tomorrow and the day after tomorrow just because this engine is what drives this success. Results are evident. results are evident We have an engine and it's running. we have an engine and it's running We are sensing the market in an industry which allows us to predict what's gonna happen next and how many people we need. we are sensing the market in an industry which allows us to predict what's gonna happen next and how many people we need It helps us to build the supply depths through our learning programs, combining formal and informal education, and then verifies the skills to be sure through the real delivery, through the production. it helps us to build the supply depths through our learning programs combining formal and informal education and then verifies the skills to be sure through the real delivery through the production We are able to deploy our people fit for purpose, right skills, right people for the right project. we are able to deploy our people fit for purpose right skills right people for the right project We can do it quickly and keeping quality. we can do it quickly and keeping quality Deploy function goes back to the sense, and that's the way how the feedback loop completes. deploy function goes back to the sense and that's the way how the feedback loop completes That's how the whole engine is working. that's how the whole engine is working We can not only today create several full stack agentic engineers, so many of them, we can do it tomorrow and the day after tomorrow just because this engine is what drives this success. we can not only today create several full stack agentic engineers so many of them we can do it tomorrow and the day after tomorrow just because this engine is what drives this success

Speaker 30: The market commonly conflates EPAM's success with our historic footprint in Eastern Europe. That has never been correct. Our roots in Eastern Europe set the highest expectations, but this talent engine that we've been telling you about all morning is what has scaled those expectations to EPAMers worldwide. In other words, our ability to provide clients with the best engineering talent is and has always been due to what we're showing you today. A platform and business model specifically designed to sense, develop, and deploy cutting-edge talent. As you have heard through the years, what defines cutting edge has changed, but the success of our model has not. We have maintained world-class talent in every era and in every area of the world. From this perspective, full stack agentic engineers are not a new challenge for us. They're just the next frontier. The market commonly conflates EPAM's success with our historic footprint in Eastern Europe. the market commonly conflates epam's success with our historic footprint in eastern europe That has never been correct. that has never been correct Our roots in Eastern Europe set the highest expectations, but this talent engine that we've been telling you about all morning is what has scaled those expectations to EPAMers worldwide. our roots in eastern europe set the highest expectations but this talent engine that we've been telling you about all morning is what has scaled those expectations to epamers worldwide In other words, our ability to provide clients with the best engineering talent is and has always been due to what we're showing you today. in other words our ability to provide clients with the best engineering talent is and has always been due to what we're showing you today A platform and business model specifically designed to sense, develop, and deploy cutting-edge talent. a platform and business model specifically designed to sense develop and deploy cutting-edge talent As you have heard through the years, what defines cutting edge has changed, but the success of our model has not. as you have heard through the years what defines cutting edge has changed but the success of our model has not We have maintained world-class talent in every era and in every area of the world. we have maintained world-class talent in every era and in every area of the world From this perspective, full stack agentic engineers are not a new challenge for us. from this perspective full stack agentic engineers are not a new challenge for us They're just the next frontier. they're just the next frontier Competitors are scrambling right now to recreate TelescopeAI and our skills-based organization, as they should. Meanwhile, we will continue to refine our engine and use it to help our clients get ahead. As you've heard all morning, AI is changing and expanding, not diminishing the need for expert engineering talent. In fact, AI has only made the need for that foundation stronger. Value follows constraints, and in a world of AI, one of the biggest constraints is human skills. To meet the moment, IT professional services organizations must sense what those skills are, motivate employees to develop them, and deploy the right combination of skills to the market. That's it. That's what it takes to lead in the IT services market. In this, EPAM has a 30-year structural built-in disadvantage. Thank you. Competitors are scrambling right now to recreate TelescopeAI and our skills-based organization, as they should. competitors are scrambling right now to recreate telescopeai and our skills-based organization as they should Meanwhile, we will continue to refine our engine and use it to help our clients get ahead. meanwhile we will continue to refine our engine and use it to help our clients get ahead As you've heard all morning, AI is changing and expanding, not diminishing the need for expert engineering talent. as you've heard all morning ai is changing and expanding not diminishing the need for expert engineering talent In fact, AI has only made the need for that foundation stronger. in fact ai has only made the need for that foundation stronger Value follows constraints, and in a world of AI, one of the biggest constraints is human skills. value follows constraints and in a world of ai one of the biggest constraints is human skills To meet the moment, IT professional services organizations must sense what those skills are, motivate employees to develop them, and deploy the right combination of skills to the market. to meet the moment it professional services organizations must sense what those skills are motivate employees to develop them and deploy the right combination of skills to the market That's it. that's it That's what it takes to lead in the IT services market. that's what it takes to lead in the it services market In this, EPAM has a 30-year structural built-in disadvantage. in this epam has a 30-year structural built-in disadvantage Thank you. thank you

Speaker 3: All right. I wanna welcome to the stage Chief People Officer, Larry Solomon. Thank you. All right. all right I wanna welcome to the stage Chief People Officer, Larry Solomon. i wanna welcome to the stage chief people officer larry solomon Thank you. thank you

Speaker 21: Hello, everyone. It's great to be here. I'm Larry Solomon, as you just heard, EPAM's Chief People Officer, and I've been in that role for coming up on 10 years now. Now, earlier in the session, you heard Adam Auerbach comment that he's been in and around the IT industry for 25 years. I've been in and around the IT industry for 40 years, approximately. Now, I know what you're all thinking, especially those in the front row. There's no way that that guy up there has 40 years of work experience under his belt, right? All right. I see a few. Okay. All right. Thank you. Thank you for that. But to get more serious, I first wanna thank you for coming today. It's much appreciated. Hello, everyone. hello everyone It's great to be here. it's great to be here I'm Larry Solomon, as you just heard, EPAM's Chief People Officer, and I've been in that role for coming up on 10 years now. i'm larry solomon as you just heard epam's chief people officer and i've been in that role for coming up on 10 years now Now, earlier in the session, you heard Adam Auerbach comment that he's been in and around the IT industry for 25 years. now earlier in the session you heard adam auerbach comment that he's been in and around the it industry for 25 years I've been in and around the IT industry for 40 years, approximately. i've been in and around the it industry for 40 years approximately Now, I know what you're all thinking, especially those in the front row. now i know what you're all thinking especially those in the front row There's no way that that guy up there has 40 years of work experience under his belt, right? there's no way that that guy up there has 40 years of work experience under his belt right All right. all right I see a few. i see a few Okay. okay All right. all right Thank you. thank you Thank you for that. thank you for that But to get more serious, I first wanna thank you for coming today. but to get more serious i first wanna thank you for coming today It's much appreciated. it's much appreciated I'm gonna quickly take you through our global talent and delivery model that has evolved over the past few years, and why that evolution has made us stronger, more resilient, and better positioned than we've ever been in the history of the company to support our clients all over the world. Our delivery model today is not only stable, it's optimized. We've built a model that's more balanced, global, and flexible than ever before, and that foundation has been what's let us scale rapidly, move talent where we need it, move talent when we need it, and deliver for our clients no matter what in the heck is going on in the world around us, and we've had a lot going on in the world around us, as you all know. I'm gonna quickly take you through our global talent and delivery model that has evolved over the past few years, and why that evolution has made us stronger, more resilient, and better positioned than we've ever been in the history of the company to support our clients all over the world. i'm gonna quickly take you through our global talent and delivery model that has evolved over the past few years and why that evolution has made us stronger more resilient and better positioned than we've ever been in the history of the company to support our clients all over the world Our delivery model today is not only stable, it's optimized. our delivery model today is not only stable it's optimized We've built a model that's more balanced, global, and flexible than ever before, and that foundation has been what's let us scale rapidly, move talent where we need it, move talent when we need it, and deliver for our clients no matter what in the heck is going on in the world around us, and we've had a lot going on in the world around us, as you all know. we've built a model that's more balanced global and flexible than ever before and that foundation has been what's let us scale rapidly move talent where we need it move talent when we need it and deliver for our clients no matter what in the heck is going on in the world around us and we've had a lot going on in the world around us as you all know Now, I like threes, so there are three key takeaways that I'd like you all to take away today. First, we've successfully rebalanced our delivery base. The 2022 invasion of Ukraine was a catalyst, an unbelievable, almost unreal, incredible catalyst that accelerated our move into nearshore and offshore hubs without sacrificing client continuity and the quality of our delivery to our clients. Let me assure you can't learn that from the fine educational institutions that we have within a few miles from where we are today. You can only learn that by experiencing it, by living it, and that's what we did. Second, it wasn't just about moving people. It was about de-risking our entire delivery execution model, and we've built a rock-solid culture of resiliency. Now, I like threes, so there are three key takeaways that I'd like you all to take away today. now i like threes so there are three key takeaways that i'd like you all to take away today First, we've successfully rebalanced our delivery base. first we've successfully rebalanced our delivery base The 2022 invasion of Ukraine was a catalyst, an unbelievable, almost unreal, incredible catalyst that accelerated our move into nearshore and offshore hubs without sacrificing client continuity and the quality of our delivery to our clients. the 2022 invasion of ukraine was a catalyst an unbelievable almost unreal incredible catalyst that accelerated our move into nearshore and offshore hubs without sacrificing client continuity and the quality of our delivery to our clients Let me assure you can't learn that from the fine educational institutions that we have within a few miles from where we are today. let me assure you can't learn that from the fine educational institutions that we have within a few miles from where we are today You can only learn that by experiencing it, by living it, and that's what we did. you can only learn that by experiencing it by living it and that's what we did Second, it wasn't just about moving people. second it wasn't just about moving people It was about de-risking our entire delivery execution model, and we've built a rock-solid culture of resiliency. it was about de-risking our entire delivery execution model and we've built a rock-solid culture of resiliency Resiliency first. Finally, we're now truly distributed around the world, harnessing the lessons that we've learned from crisis. Fortunately or unfortunately, crises have become a core competency of ours. It's helped us create a global engine that provides better access to top talent, and you've heard about the importance of top talent, and you'll hear about it today after me. This is now a durable competitive advantage for our enterprise. Now, to understand where we are today, you need to look at where we came from, where we started. Back a few years ago, in late 2021, we were already in the process of diversifying. As many of you that have followed us know, our footprint was still quite heavily concentrated. Resiliency first. Finally, we're now truly distributed around the world, harnessing the lessons that we've learned from crisis. resiliency first. finally we're now truly distributed around the world harnessing the lessons that we've learned from crisis Fortunately or unfortunately, crises have become a core competency of ours. fortunately or unfortunately crises have become a core competency of ours It's helped us create a global engine that provides better access to top talent, and you've heard about the importance of top talent, and you'll hear about it today after me. it's helped us create a global engine that provides better access to top talent and you've heard about the importance of top talent and you'll hear about it today after me This is now a durable competitive advantage for our enterprise. this is now a durable competitive advantage for our enterprise Now, to understand where we are today, you need to look at where we came from, where we started. now to understand where we are today you need to look at where we came from where we started Back a few years ago, in late 2021, we were already in the process of diversifying. back a few years ago in late 2021 we were already in the process of diversifying As many of you that have followed us know, our footprint was still quite heavily concentrated. as many of you that have followed us know our footprint was still quite heavily concentrated At that time, 59% of our delivery professionals, 52,000 strong at that time, were based in three countries, and you probably know them, Belarus, Ukraine and Russia. While this served us well for many, many years, it represented geographic concentration risk that we knew we absolutely had to address and deal with. Let's fast-forward now. A few months ago, the end of 2025. Look at the shift in the circles on the map here. Our delivery force has grown to almost 57,000 production professionals, but the distribution of where they are around the world is like night and day. We've reduced our concentration in Ukraine and Belarus by 38%, and at the same time, we aggressively ramped up other parts of the world like India, Latin America and Western and Central Asia. This is what optimized and balanced looks like. At that time, 59% of our delivery professionals, 52,000 strong at that time, were based in three countries, and you probably know them, Belarus, Ukraine and Russia. at that time 59% of our delivery professionals 52,000 strong at that time were based in three countries and you probably know them belarus ukraine and russia While this served us well for many, many years, it represented geographic concentration risk that we knew we absolutely had to address and deal with. while this served us well for many many years it represented geographic concentration risk that we knew we absolutely had to address and deal with Let's fast-forward now. let's fast-forward now A few months ago, the end of 2025. a few months ago the end of 2025 Look at the shift in the circles on the map here. look at the shift in the circles on the map here Our delivery force has grown to almost 57,000 production professionals, but the distribution of where they are around the world is like night and day. our delivery force has grown to almost 57,000 production professionals but the distribution of where they are around the world is like night and day We've reduced our concentration in Ukraine and Belarus by 38%, and at the same time, we aggressively ramped up other parts of the world like India, Latin America and Western and Central Asia. we've reduced our concentration in ukraine and belarus by 38% and at the same time we aggressively ramped up other parts of the world like india latin america and western and central asia This is what optimized and balanced looks like. this is what optimized and balanced looks like We're no longer dependent on any single geography, on any single region. We're much more regionally balanced and diversified today. Now, I'm extremely proud of how fast our teams pivoted. We have a saying that we use quite often around the place, "Speed kills when you don't have it." We had it, and we still do today more than ever. We relocated people, we opened up brand-new locations, we expanded our mobility programs, and we built talent pipelines in new markets, all at a pace that no other company could match. This speed and agility is absolutely part of the core of what and who EPAM is today. Today the model is a real strategic advantage for us. It helps us deploy the right skills to the right clients in the right places at the right times. We're no longer dependent on any single geography, on any single region. we're no longer dependent on any single geography on any single region We're much more regionally balanced and diversified today. we're much more regionally balanced and diversified today Now, I'm extremely proud of how fast our teams pivoted. now i'm extremely proud of how fast our teams pivoted We have a saying that we use quite often around the place, "Speed kills when you don't have it." We had it, and we still do today more than ever. we have a saying that we use quite often around the place "speed kills when you don't have it." we had it and we still do today more than ever We relocated people, we opened up brand-new locations, we expanded our mobility programs, and we built talent pipelines in new markets, all at a pace that no other company could match. we relocated people we opened up brand-new locations we expanded our mobility programs and we built talent pipelines in new markets all at a pace that no other company could match This speed and agility is absolutely part of the core of what and who EPAM is today. this speed and agility is absolutely part of the core of what and who epam is today Today the model is a real strategic advantage for us. today the model is a real strategic advantage for us It helps us deploy the right skills to the right clients in the right places at the right times. it helps us deploy the right skills to the right clients in the right places at the right times It improves our cost positioning. It expands our access to top talent and gives us the geographic flexibility that is extremely difficult to replace. We're poised to capitalize on this more balanced footprint. We've de-risked our execution with stronger business continuity. We have better and faster talent access from a much wider pool of specialized and unique skills that our clients are demanding from us every day. As you'll hear from others, we're integrating AI-enabled optimizations across our company to improve our cost profile and utilization across the regions. Ultimately, the model that we're talking about here supports an important 24/7 or follow-the-sun delivery cycle, and that creates faster iterations and turns for our clients. Today, we find ourselves even faster, safer and more globally diversified than at any point in the company's history. It improves our cost positioning. it improves our cost positioning It expands our access to top talent and gives us the geographic flexibility that is extremely difficult to replace. it expands our access to top talent and gives us the geographic flexibility that is extremely difficult to replace We're poised to capitalize on this more balanced footprint. we're poised to capitalize on this more balanced footprint We've de-risked our execution with stronger business continuity. we've de-risked our execution with stronger business continuity We have better and faster talent access from a much wider pool of specialized and unique skills that our clients are demanding from us every day. we have better and faster talent access from a much wider pool of specialized and unique skills that our clients are demanding from us every day As you'll hear from others, we're integrating AI-enabled optimizations across our company to improve our cost profile and utilization across the regions. as you'll hear from others we're integrating ai-enabled optimizations across our company to improve our cost profile and utilization across the regions Ultimately, the model that we're talking about here supports an important 24/7 or follow-the-sun delivery cycle, and that creates faster iterations and turns for our clients. ultimately the model that we're talking about here supports an important 24/7 or follow-the-sun delivery cycle and that creates faster iterations and turns for our clients Today, we find ourselves even faster, safer and more globally diversified than at any point in the company's history. today we find ourselves even faster safer and more globally diversified than at any point in the company's history Now, some of you may recall, the concluding comment that I made at these events in prior years, and I'm gonna say it again today, so it's okay if you don't recall. I'm gonna say it again today 'cause I believe it's more true now than it ever has been. We hold the cards that we've been dealt, and I wouldn't trade in our hand for anything. With that, I am excited and delighted to hand over to my good friend, my colleague, and frankly, one of the most talented and smartest leaders that I've had the privilege of working with in my 10 years at EPAM, Victor Dvorkin. Thank you very much. Now, some of you may recall, the concluding comment that I made at these events in prior years, and I'm gonna say it again today, so it's okay if you don't recall. now some of you may recall the concluding comment that i made at these events in prior years and i'm gonna say it again today so it's okay if you don't recall I'm gonna say it again today 'cause I believe it's more true now than it ever has been. i'm gonna say it again today 'cause i believe it's more true now than it ever has been We hold the cards that we've been dealt, and I wouldn't trade in our hand for anything. we hold the cards that we've been dealt and i wouldn't trade in our hand for anything With that, I am excited and delighted to hand over to my good friend, my colleague, and frankly, one of the most talented and smartest leaders that I've had the privilege of working with in my 10 years at EPAM, Victor Dvorkin. with that i am excited and delighted to hand over to my good friend my colleague and frankly one of the most talented and smartest leaders that i've had the privilege of working with in my 10 years at epam victor dvorkin Thank you very much. thank you very much

Speaker 34: Thank you, Larry. Yeah, it will be hard for me to prove it. Good morning, everyone. I am with the company for 28 years, in the role for 10, and I will try to prove as a scientist that what we built is actually one of the best delivery engines in the industry, and that it will be actually rewarded by a native wave. Let's start. First, clearly enterprises got access to really powerful models right now. There is no doubt. What it means, that the demand for AI work will increase because they will understand better, they will want better, and they will ask us to do more. We spent the whole morning talking about enterprise complexity, legacy systems, complex platforms, integrations, hallucinations, we didn't talk about that, and real operating pressure which they have. This has been our environment for so many years. Thank you, Larry. thank you larry Yeah, it will be hard for me to prove it. yeah it will be hard for me to prove it Good morning, everyone. I am with the company for 28 years, in the role for 10, and I will try to prove as a scientist that what we built is actually one of the best delivery engines in the industry, and that it will be actually rewarded by a native wave. good morning everyone. i am with the company for 28 years in the role for 10 and i will try to prove as a scientist that what we built is actually one of the best delivery engines in the industry and that it will be actually rewarded by a native wave Let's start. let's start First, clearly enterprises got access to really powerful models right now. first clearly enterprises got access to really powerful models right now There is no doubt. there is no doubt What it means, that the demand for AI work will increase because they will understand better, they will want better, and they will ask us to do more. what it means that the demand for ai work will increase because they will understand better they will want better and they will ask us to do more We spent the whole morning talking about enterprise complexity, legacy systems, complex platforms, integrations, hallucinations, we didn't talk about that, and real operating pressure which they have. we spent the whole morning talking about enterprise complexity legacy systems complex platforms integrations hallucinations we didn't talk about that and real operating pressure which they have This has been our environment for so many years. this has been our environment for so many years Large transformations, regulated industries, complex platform engineering, and also Google-scale product engineering at speed. This is actually how we won the digital wave in the past. Great models for us, in our opinion, is an opportunity because this is what makes our delivery engine actually unique, and that what will make AI run the enterprise. I will show you most probably one of the most complex slides, so bear with me. Larry spoke about our location strategy. Our location strategy is a serious advantage. I'm showing you an example of a large client. They have a headquarters in U.S., a headquarters in Europe, a local GCC, and a Latin American subsidiary. Think about the complexity. We have nearly unlimited flexibility how to configure this type of engagements, meeting the most strategic, regulatory, and pricing needs of our clients. Large transformations, regulated industries, complex platform engineering, and also Google-scale product engineering at speed. large transformations regulated industries complex platform engineering and also google-scale product engineering at speed This is actually how we won the digital wave in the past. this is actually how we won the digital wave in the past Great models for us, in our opinion, is an opportunity because this is what makes our delivery engine actually unique, and that what will make AI run the enterprise. great models for us in our opinion is an opportunity because this is what makes our delivery engine actually unique and that what will make ai run the enterprise I will show you most probably one of the most complex slides, so bear with me. i will show you most probably one of the most complex slides so bear with me Larry spoke about our location strategy. larry spoke about our location strategy Our location strategy is a serious advantage. our location strategy is a serious advantage I'm showing you an example of a large client. i'm showing you an example of a large client They have a headquarters in U.S., a headquarters in Europe, a local GCC, and a Latin American subsidiary. they have a headquarters in u.s a headquarters in europe a local gcc and a latin american subsidiary Think about the complexity. think about the complexity We have nearly unlimited flexibility how to configure this type of engagements, meeting the most strategic, regulatory, and pricing needs of our clients. we have nearly unlimited flexibility how to configure this type of engagements meeting the most strategic regulatory and pricing needs of our clients We, as Sandra and Alexis said, we sense, develop, and deploy our talent. I will add, we also continuously assess our talent globally and unify our skills globally through global unified assessments. Every engineer, in order to get promoted, need to be assessed from an engineer actually to an SVP. We just finished the cycle right now. This consistency is a key. I will complicate the slide more. Data practice. As you see, it's global. It's in every location. This is our major strength, as well as cloud, digital and product engineering, SAP, Salesforce, and other practices. This horizontal capability is massive, with thousands of professionals, leadership, competency centers, partnership with cloud and platform providers, methods, tooling, training, certifications, and operations. I will complicate the picture more. I will add verticals. By the way, talking about hallucinations. In healthcare, they produce unsafe outputs. We, as Sandra and Alexis said, we sense, develop, and deploy our talent. we as sandra and alexis said we sense develop and deploy our talent I will add, we also continuously assess our talent globally and unify our skills globally through global unified assessments. i will add we also continuously assess our talent globally and unify our skills globally through global unified assessments Every engineer, in order to get promoted, need to be assessed from an engineer actually to an SVP. every engineer in order to get promoted need to be assessed from an engineer actually to an svp We just finished the cycle right now. we just finished the cycle right now This consistency is a key. this consistency is a key I will complicate the slide more. i will complicate the slide more Data practice. data practice As you see, it's global. as you see it's global It's in every location. it's in every location This is our major strength, as well as cloud, digital and product engineering, SAP, Salesforce, and other practices. this is our major strength as well as cloud digital and product engineering sap salesforce and other practices This horizontal capability is massive, with thousands of professionals, leadership, competency centers, partnership with cloud and platform providers, methods, tooling, training, certifications, and operations. this horizontal capability is massive with thousands of professionals leadership competency centers partnership with cloud and platform providers methods tooling training certifications and operations I will complicate the picture more. i will complicate the picture more I will add verticals. i will add verticals By the way, talking about hallucinations. by the way talking about hallucinations In healthcare, they produce unsafe outputs. in healthcare they produce unsafe outputs In financial services, non-compliant responses. In supply chain, the output looks great, but think about the world. It will not work today. That's why vertical is super important. That's why T-shaped talent matters the most for AI adoption. That's why organically, with our clients together and through acquisitions, we are continuing to develop vertical capability. Elaina and Eli spoke about consultants. I will talk about engineers. Think about healthcare, life sciences, financial services, media, gaming, more. T-shaped talent makes system work with AI. Think about now three deep pictures we just covered, right? It is absolutely unrealistic to run this manually. That's why for so many years we developed our digital ecosystem, covering talent, skills, knowledge, technology, and I will show you delivery. This is a delivery view of a delivery engine. See? It looks fine. Green. In financial services, non-compliant responses. in financial services non-compliant responses In supply chain, the output looks great, but think about the world. in supply chain the output looks great but think about the world It will not work today. it will not work today That's why vertical is super important. that's why vertical is super important That's why T-shaped talent matters the most for AI adoption. that's why t-shaped talent matters the most for ai adoption That's why organically, with our clients together and through acquisitions, we are continuing to develop vertical capability. that's why organically with our clients together and through acquisitions we are continuing to develop vertical capability Elaina and Eli spoke about consultants. elaina and eli spoke about consultants I will talk about engineers. i will talk about engineers Think about healthcare, life sciences, financial services, media, gaming, more. think about healthcare life sciences financial services media gaming more T-shaped talent makes system work with AI. t-shaped talent makes system work with ai Think about now three deep pictures we just covered, right? think about now three deep pictures we just covered right It is absolutely unrealistic to run this manually. it is absolutely unrealistic to run this manually That's why for so many years we developed our digital ecosystem, covering talent, skills, knowledge, technology, and I will show you delivery. that's why for so many years we developed our digital ecosystem covering talent skills knowledge technology and i will show you delivery This is a delivery view of a delivery engine. this is a delivery view of a delivery engine See? see It looks fine. it looks fine Green. green I actually would say it's a bit too much green. That's why we will drill down on a specific account. What we can see. Through AI-powered systems, we can now instantly understand what risk we are doing, what type of analysis we should have, and how to remediate the problem. This also accumulates our reusable delivery knowledge, which helps us with estimates and with many other things. The same view through the agent. You can see that agents and teams can query it from Claude Code or from other environment, or actually through the agentic factory. This is coming. The Vic bot. Yeah, it's me. I forgot the glasses. How to explain Vic bot? That's very easy. If you have a red project, Vc bot will come to you. That's how it was explained to me somewhere in the kitchen. Yeah. I actually would say it's a bit too much green. i actually would say it's a bit too much green That's why we will drill down on a specific account. that's why we will drill down on a specific account What we can see. what we can see Through AI-powered systems, we can now instantly understand what risk we are doing, what type of analysis we should have, and how to remediate the problem. through ai-powered systems we can now instantly understand what risk we are doing what type of analysis we should have and how to remediate the problem This also accumulates our reusable delivery knowledge, which helps us with estimates and with many other things. this also accumulates our reusable delivery knowledge which helps us with estimates and with many other things The same view through the agent. the same view through the agent You can see that agents and teams can query it from Claude Code or from other environment, or actually through the agentic factory. you can see that agents and teams can query it from claude code or from other environment or actually through the agentic factory This is coming. this is coming The Vic bot. the vic bot Yeah, it's me. yeah it's me I forgot the glasses. i forgot the glasses How to explain Vic bot? how to explain vic bot That's very easy. that's very easy If you have a red project, Vc bot will come to you. if you have a red project vc bot will come to you That's how it was explained to me somewhere in the kitchen. Yeah. that's how it was explained to me somewhere in the kitchen. yeah Most interesting, we both also work on our newly built AI factory, which we can demonstrate today. It helps to validate our proposals, it helps to check the estimates and the value we bring to our clients. With that, I will leave you with a few things for everybody. We have really advanced capabilities, global scale, consistent standards, T-shaped expertise, and AI-run platform which runs our delivery engine, which runs the enterprise, and which will be ready to win the AI wave. With that, actually, I have one more thing. To feel the organization's heartbeat, we prepared a panel with leaders building and running teams around EPAM. I would like to welcome Amit Singhal, Head of European Delivery, to introduce the panel. Thank you. Most interesting, we both also work on our newly built AI factory, which we can demonstrate today. most interesting we both also work on our newly built ai factory which we can demonstrate today It helps to validate our proposals, it helps to check the estimates and the value we bring to our clients. it helps to validate our proposals it helps to check the estimates and the value we bring to our clients With that, I will leave you with a few things for everybody. with that i will leave you with a few things for everybody We have really advanced capabilities, global scale, consistent standards, T-shaped expertise, and AI-run platform which runs our delivery engine, which runs the enterprise, and which will be ready to win the AI wave. we have really advanced capabilities global scale consistent standards t-shaped expertise and ai-run platform which runs our delivery engine which runs the enterprise and which will be ready to win the ai wave With that, actually, I have one more thing. with that actually i have one more thing To feel the organization's heartbeat, we prepared a panel with leaders building and running teams around EPAM. to feel the organization's heartbeat we prepared a panel with leaders building and running teams around epam I would like to welcome Amit Singhal, Head of European Delivery, to introduce the panel. i would like to welcome amit singhal head of european delivery to introduce the panel Thank you. thank you

Speaker 4: Thank you, Vik. By the way, that big bot is real. It's calling me every day. It's much nicer him calling than Vik calling me. My name is Amit Singhal, SVP and Head of Delivery for EPAM in Europe. Joined EPAM roughly 10 years back, but who's counting? As Vik said, I'm gonna host a panel for you so you can hear from some of our regional leaders. Please join me in welcoming them. Okay. How are you all doing? Thank you, Vik. thank you vik By the way, that big bot is real. by the way that big bot is real It's calling me every day. it's calling me every day It's much nicer him calling than Vik calling me. it's much nicer him calling than vik calling me My name is Amit Singhal, SVP and Head of Delivery for EPAM in Europe. my name is amit singhal svp and head of delivery for epam in europe Joined EPAM roughly 10 years back, but who's counting? joined epam roughly 10 years back but who's counting As Vik said, I'm gonna host a panel for you so you can hear from some of our regional leaders. as vik said i'm gonna host a panel for you so you can hear from some of our regional leaders Please join me in welcoming them. please join me in welcoming them Okay. okay How are you all doing? how are you all doing

Speaker 13: Great. Great. great

Speaker 31: Very well. Very well. very well

Speaker 4: Yeah. Yeah. yeah

Speaker 23: Amazing. Amazing. amazing

Speaker 4: Okay. Sitting at the far end is Enver, my partner in crime in Europe. Okay. okay Sitting at the far end is Enver, my partner in crime in Europe. sitting at the far end is enver my partner in crime in europe

Speaker 13: Hi. Hello. Hi. hi Hello. hello

Speaker 4: Maybe we should have sat together, but it's okay. Enver heads our business in Europe. By the way, congratulations on getting to the top place in Whitelane survey in Europe. Maybe we should have sat together, but it's okay. maybe we should have sat together but it's okay Enver heads our business in Europe. enver heads our business in europe By the way, congratulations on getting to the top place in Whitelane survey in Europe. by the way congratulations on getting to the top place in whitelane survey in europe

Speaker 13: Thank you. Thank you. thank you

Speaker 4: You and I both seeing an interesting trend in Europe where business is growing much more rapidly than we hope. We like it, but we had hoped. You and I both seeing an interesting trend in Europe where business is growing much more rapidly than we hope. you and i both seeing an interesting trend in europe where business is growing much more rapidly than we hope We like it, but we had hoped. we like it but we had hoped

Speaker 13: We do. We do. we do

Speaker 4: Yeah. Across sectors and industries. Hope that's not an accident, and there is a strategy behind it. Keen to hear from you, what's going on there. Next to Enver is Srinivas, Srini, as we fondly call him. You and I joined roughly the same time in EPAM. That's right. Your mission was to build a different kind of India for EPAM, in the region and scale it. It's one of the largest location now, so you must have done something right, Srini. Yeah. Congratulations and welcome. Yeah. yeah Across sectors and industries. across sectors and industries Hope that's not an accident, and there is a strategy behind it. hope that's not an accident and there is a strategy behind it Keen to hear from you, what's going on there. keen to hear from you what's going on there Next to Enver is Srinivas, Srini, as we fondly call him. next to enver is srinivas srini as we fondly call him You and I joined roughly the same time in EPAM. you and i joined roughly the same time in epam That's right. that's right Your mission was to build a different kind of India for EPAM, in the region and scale it. your mission was to build a different kind of india for epam in the region and scale it It's one of the largest location now, so you must have done something right, Srini. it's one of the largest location now so you must have done something right srini Yeah. yeah Congratulations and welcome. congratulations and welcome

Speaker 31: Thank you. Thank you. thank you

Speaker 4: You took a long flight to get to Boston. You took a long flight to get to Boston. you took a long flight to get to boston

Speaker 31: I did. I did. i did

Speaker 4: Through a narrow air corridor. Through a narrow air corridor. through a narrow air corridor

Speaker 31: That's right. Over Iran. That's right. that's right Over Iran. over iran

Speaker 4: Good. Martin. Good. good Martin. martin

Speaker 23: Hello. Hello. hello

Speaker 4: New kid on the block. New kid on the block. new kid on the block

Speaker 23: Hi. Hi. hi

Speaker 4: Very new to EPAM leadership team. Martin, you were born in... Very new to EPAM leadership team. very new to epam leadership team Martin, you were born in... martin you were born in

Speaker 23: Argentina. Argentina. argentina

Speaker 4: Argentina. You lived in Brazil and Mexico. Argentina. argentina You lived in Brazil and Mexico. you lived in brazil and mexico

Speaker 23: Yep. Yep. yep

Speaker 4: You know the region a little bit. You know the region a little bit. you know the region a little bit

Speaker 23: A little bit. A little bit. a little bit

Speaker 4: You're enjoying your journey so far with EPAM? You're enjoying your journey so far with EPAM? you're enjoying your journey so far with epam

Speaker 23: Very much. Very much. very much

Speaker 4: Okay. Just much like Srini, Martin joined us to consolidate our investment in the region and create one team which can be plugged into a global delivery model that Vik talked about. Welcome, Martin. Okay. okay Just much like Srini, Martin joined us to consolidate our investment in the region and create one team which can be plugged into a global delivery model that Vik talked about. just much like srini martin joined us to consolidate our investment in the region and create one team which can be plugged into a global delivery model that vik talked about Welcome, Martin. welcome martin

Speaker 23: Thank you. Thank you. thank you

Speaker 4: Last but not the least, Stepan. Stepan leads our teams in Ukraine, and all of us know, the war is still ongoing and everything that throws at Stephan and his team, and you continue to do good work. On behalf of entire EPAM family and our clients, Stepan, can I say thank you. Thank you very much. Last but not the least, Stepan. last but not the least stepan Stepan leads our teams in Ukraine, and all of us know, the war is still ongoing and everything that throws at Stephan and his team, and you continue to do good work. stepan leads our teams in ukraine and all of us know the war is still ongoing and everything that throws at stephan and his team and you continue to do good work On behalf of entire EPAM family and our clients, Stepan, can I say thank you. on behalf of entire epam family and our clients stepan can i say thank you Thank you very much. thank you very much

Speaker 32: Thank you. Thanks for having me. Thank you. thank you Thanks for having me. thanks for having me

Speaker 4: Thank you. That's amazing. Thank you, all. Let's get into it. There's a lot to talk about, but let's try and focus on few things. I'm very keen to talk about resilience of EPAM delivery, how GenAI adoption is going across complex enterprises, how do we balance our global mindset, but equally, Srinivas, for example, in your case, working locally with GCC. Enver, if I could start with you. Thank you. thank you That's amazing. that's amazing Thank you, all. thank you all Let's get into it. let's get into it There's a lot to talk about, but let's try and focus on few things. there's a lot to talk about but let's try and focus on few things I'm very keen to talk about resilience of EPAM delivery, how GenAI adoption is going across complex enterprises, how do we balance our global mindset, but equally, Srinivas, for example, in your case, working locally with GCC. i'm very keen to talk about resilience of epam delivery how genai adoption is going across complex enterprises how do we balance our global mindset but equally srinivas for example in your case working locally with gcc Enver, if I could start with you. enver if i could start with you

Speaker 13: Sure. Sure. sure

Speaker 4: You and I know Europe is a melting pot of cultures and languages, and it's fragmented. There are complexities. How do you lean on big EPAM to deliver best-in-class services for them? You and I know Europe is a melting pot of cultures and languages, and it's fragmented. you and i know europe is a melting pot of cultures and languages and it's fragmented There are complexities. there are complexities How do you lean on big EPAM to deliver best-in-class services for them? how do you lean on big epam to deliver best-in-class services for them

Speaker 13: Thank you, Amit. Indeed, Europe is a great mix of cultures and languages. A place from where a number of global companies are rooted. Also a significant market for a number of localized businesses. As Vik and Larry said, we as a company invested heavily into reinforcing our global delivery engine so we can serve clients from everywhere in the world. At the same time, working for a number of years with our clients, shoulder to shoulder, we accumulate a significant amount of industry knowledge. Today, I believe our winning combination is in-market Western European talents for client proximity, senior leadership and regulatory alignment. Thank you, Amit. thank you amit Indeed, Europe is a great mix of cultures and languages. indeed europe is a great mix of cultures and languages A place from where a number of global companies are rooted. a place from where a number of global companies are rooted Also a significant market for a number of localized businesses. also a significant market for a number of localized businesses As Vik and Larry said, we as a company invested heavily into reinforcing our global delivery engine so we can serve clients from everywhere in the world. as vik and larry said we as a company invested heavily into reinforcing our global delivery engine so we can serve clients from everywhere in the world At the same time, working for a number of years with our clients, shoulder to shoulder, we accumulate a significant amount of industry knowledge. at the same time working for a number of years with our clients shoulder to shoulder we accumulate a significant amount of industry knowledge Today, I believe our winning combination is in-market Western European talents for client proximity, senior leadership and regulatory alignment. today i believe our winning combination is in-market western european talents for client proximity senior leadership and regulatory alignment Eastern European teams or nearshore teams for in-depth engineering talent and for business knowledge, and offshore teams for technical talent for scale and cost-efficient execution. If you add on top of this, mature governance and now AI-powered productivity gains, then you get an engine which is both resilient and highly efficient. Eastern European teams or nearshore teams for in-depth engineering talent and for business knowledge, and offshore teams for technical talent for scale and cost-efficient execution. eastern european teams or nearshore teams for in-depth engineering talent and for business knowledge and offshore teams for technical talent for scale and cost-efficient execution If you add on top of this, mature governance and now AI-powered productivity gains, then you get an engine which is both resilient and highly efficient. if you add on top of this mature governance and now ai-powered productivity gains then you get an engine which is both resilient and highly efficient

Speaker 4: Right team supplied in the right proportions at the right time. Right team supplied in the right proportions at the right time. right team supplied in the right proportions at the right time

Speaker 13: Absolutely Absolutely absolutely

Speaker 4: To the right situation is the winning combination. Martin, if I could come to you next. Bit similar to what Enver said, but we know Latin America is your backyard, so you know it better than the rest of us. What's your sort of winning combination in the region, both for your local customers, which you brought with you from Neoris, and plus EPAM global customers? To the right situation is the winning combination. to the right situation is the winning combination Martin, if I could come to you next. martin if i could come to you next Bit similar to what Enver said, but we know Latin America is your backyard, so you know it better than the rest of us. bit similar to what enver said but we know latin america is your backyard so you know it better than the rest of us What's your sort of winning combination in the region, both for your local customers, which you brought with you from Neoris, and plus EPAM global customers? what's your sort of winning combination in the region both for your local customers which you brought with you from neoris and plus epam global customers

Speaker 23: Thank you, Amit. A pleasure to be here. It has been almost a year and a half since Neoris became part of EPAM, I think that due to that we have a much stronger EPAM in Iberoamérica. I'm glad to see that. The reason is that because we now have great engineers, plus all the AI platforms that EPAM build. Plus now we have a strong leadership team based in the region that know the region for a while. We also have a strong installed base of customers that were born in Latin America or they are playing in Latin America. As Larry, I like the threes, but I need to tell you four things, four avenues that we are pursuing in Latin America. Thank you, Amit. thank you amit A pleasure to be here. a pleasure to be here It has been almost a year and a half since Neoris became part of EPAM, I think that due to that we have a much stronger EPAM in Iberoamérica. it has been almost a year and a half since neoris became part of epam i think that due to that we have a much stronger epam in iberoamérica I'm glad to see that. i'm glad to see that The reason is that because we now have great engineers, plus all the AI platforms that EPAM build. the reason is that because we now have great engineers plus all the ai platforms that epam build Plus now we have a strong leadership team based in the region that know the region for a while. plus now we have a strong leadership team based in the region that know the region for a while We also have a strong installed base of customers that were born in Latin America or they are playing in Latin America. we also have a strong installed base of customers that were born in latin america or they are playing in latin america As Larry, I like the threes, but I need to tell you four things, four avenues that we are pursuing in Latin America. as larry i like the threes but i need to tell you four things four avenues that we are pursuing in latin america The first one is the one that EPAM was pursuing since the beginning is how to supply or how to do near-shore from Latin America to the US, and that's something that we are continue growing and developing more capabilities. Those employees or those consultants are working with us are also gonna be able to serve our local customers in Latin America. The second avenue is how to bring those new technologies that we are building on a global basis to our install base in Latin America. We are very proud now to have, I say, the Navy SEALs that will help us to expand our presence in the region. We have the platforms. The first one is the one that EPAM was pursuing since the beginning is how to supply or how to do near-shore from Latin America to the US, and that's something that we are continue growing and developing more capabilities. the first one is the one that epam was pursuing since the beginning is how to supply or how to do near-shore from latin america to the us and that's something that we are continue growing and developing more capabilities Those employees or those consultants are working with us are also gonna be able to serve our local customers in Latin America. those employees or those consultants are working with us are also gonna be able to serve our local customers in latin america The second avenue is how to bring those new technologies that we are building on a global basis to our install base in Latin America. the second avenue is how to bring those new technologies that we are building on a global basis to our install base in latin america We are very proud now to have, I say, the Navy SEALs that will help us to expand our presence in the region. we are very proud now to have i say the navy seals that will help us to expand our presence in the region We have the platforms. we have the platforms

Speaker 4: We surely need more of them. We surely need more of them. we surely need more of them

Speaker 23: Yeah. This is something that we in the past story of Neoris we were not having. I'm very proud now we are. I think that we are gonna be very successful on bringing those things to Iberoamérica. The third avenue is that we also have global customers that we are having operations in Latin America, but we were not able to serve in the past. Now we are working with them. We are helping them to deploy those technologies in Latin America. You know that Brazil, for example, is a very complex country, and we do have an operation there, and we are getting to know them and expand that relation. Yeah. yeah This is something that we in the past story of Neoris we were not having. this is something that we in the past story of neoris we were not having I'm very proud now we are. i'm very proud now we are I think that we are gonna be very successful on bringing those things to Iberoamérica. i think that we are gonna be very successful on bringing those things to iberoamérica The third avenue is that we also have global customers that we are having operations in Latin America, but we were not able to serve in the past. the third avenue is that we also have global customers that we are having operations in latin america but we were not able to serve in the past Now we are working with them. now we are working with them We are helping them to deploy those technologies in Latin America. we are helping them to deploy those technologies in latin america You know that Brazil, for example, is a very complex country, and we do have an operation there, and we are getting to know them and expand that relation. you know that brazil for example is a very complex country and we do have an operation there and we are getting to know them and expand that relation Fourth, we also have a very established relationship with a lot of the large technological partners, and they were demanding and kind of how EPAM was able to go with them to the region. Now we are partnering with all of them, and I think that's gonna be another fourth avenue that we will explore in order to grow in the region. I'm very happy to see this combination as a winning one. Fourth, we also have a very established relationship with a lot of the large technological partners, and they were demanding and kind of how EPAM was able to go with them to the region. fourth we also have a very established relationship with a lot of the large technological partners and they were demanding and kind of how epam was able to go with them to the region Now we are partnering with all of them, and I think that's gonna be another fourth avenue that we will explore in order to grow in the region. now we are partnering with all of them and i think that's gonna be another fourth avenue that we will explore in order to grow in the region I'm very happy to see this combination as a winning one. i'm very happy to see this combination as a winning one

Speaker 4: Yeah. You said something very interesting that if you want to be resilient in the global world, one of the critical item is to have a strong leadership based locally. Okay, great. Stepan. Yeah. yeah You said something very interesting that if you want to be resilient in the global world, one of the critical item is to have a strong leadership based locally. you said something very interesting that if you want to be resilient in the global world one of the critical item is to have a strong leadership based locally Okay, great. okay great Stepan. stepan

Speaker 32: Yes. Yes. yes

Speaker 4: I've got so many things I want to ask you, but time is limited. I can see it there. First of all, like, there is hardly a week goes by where I don't come across a customer who's been working with your teams in Ukraine, and all I hear is great words, and I know it's not just sympathy. On the other hand, when I talk to your people, I see motivation, I see high degree of engagement. What's the secret sauce? What's going on in the middle? I've got so many things I want to ask you, but time is limited. i've got so many things i want to ask you but time is limited I can see it there. i can see it there First of all, like, there is hardly a week goes by where I don't come across a customer who's been working with your teams in Ukraine, and all I hear is great words, and I know it's not just sympathy. first of all like there is hardly a week goes by where i don't come across a customer who's been working with your teams in ukraine and all i hear is great words and i know it's not just sympathy On the other hand, when I talk to your people, I see motivation, I see high degree of engagement. on the other hand when i talk to your people i see motivation i see high degree of engagement What's the secret sauce? what's the secret sauce What's going on in the middle? what's going on in the middle

Speaker 32: Thank you, Amit. I think that's the most common question I get asked. First of all the credits should go to Ukrainian team. They are awesome, brave, resilient, and I'm really proud to be part of it. Now, answering your question, I think there are several components that help us to be successful. First and foremost, I believe that we secured the foundation. Basically, company stood with us from the day one. They created a $100 million dedicated fund to help our people, their family. You know, there is an expression, you want your employee to take care about your clients, take care about your employees, and that's exactly what we did. Thank you, Amit. thank you amit I think that's the most common question I get asked. i think that's the most common question i get asked First of all the credits should go to Ukrainian team. first of all the credits should go to ukrainian team They are awesome, brave, resilient, and I'm really proud to be part of it. they are awesome brave resilient and i'm really proud to be part of it Now, answering your question, I think there are several components that help us to be successful. now answering your question i think there are several components that help us to be successful First and foremost, I believe that we secured the foundation. first and foremost i believe that we secured the foundation Basically, company stood with us from the day one. basically company stood with us from the day one They created a $100 million dedicated fund to help our people, their family. they created a $100 million dedicated fund to help our people their family You know, there is an expression, you want your employee to take care about your clients, take care about your employees, and that's exactly what we did. you know there is an expression you want your employee to take care about your clients take care about your employees and that's exactly what we did Second, I think we focus on the purpose, not the pity, and that might be not obvious for people outside Ukraine, but for Ukrainians, the biggest motivation is feeling yourself useful. You can protect country in trenches, or you can protect country on economic front. I remember a conversation with a client, like, who was kind of reluctant to open work for Ukrainian teams just out of a sympathy. Well, kind of, he told me, "Stephan, I cannot push your people to war during wartime." I told him, "Well, while I appreciate your heart, but the truth is that our people has a tremendous motivation to work because it brings revenue, it increases taxes, you know, it helps to protect, like, working places, IT industry, et cetera. Second, I think we focus on the purpose, not the pity, and that might be not obvious for people outside Ukraine, but for Ukrainians, the biggest motivation is feeling yourself useful. second i think we focus on the purpose not the pity and that might be not obvious for people outside ukraine but for ukrainians the biggest motivation is feeling yourself useful You can protect country in trenches, or you can protect country on economic front. you can protect country in trenches or you can protect country on economic front I remember a conversation with a client, like, who was kind of reluctant to open work for Ukrainian teams just out of a sympathy. i remember a conversation with a client like who was kind of reluctant to open work for ukrainian teams just out of a sympathy Well, kind of, he told me, "Stephan, I cannot push your people to war during wartime." I told him, "Well, while I appreciate your heart, but the truth is that our people has a tremendous motivation to work because it brings revenue, it increases taxes, you know, it helps to protect, like, working places, IT industry, et cetera. well kind of he told me "stephan i cannot push your people to war during wartime." i told him "well while i appreciate your heart but the truth is that our people has a tremendous motivation to work because it brings revenue it increases taxes you know it helps to protect like working places it industry et cetera That purpose gives our people control while kind of everything else is volatile. He was like, "Whoa, I didn't think about that from that angle." That was eye-opener for him. He opened, like, work for our teams, and they've been delivering for him ever since. Last but not least, I believe it's our results relentlessly attitude. You know, London Stock Exchange, our huge client. They have a massive, like, program of migrating hundreds of applications from on-prem to Azure. By the way, like, several previous attempts failed with other vendors. Just recently, we completed a first migration of the application that was done by a small Ukrainian team with a little bit of a sleepless nights, of course, with the usage of AI. That purpose gives our people control while kind of everything else is volatile. that purpose gives our people control while kind of everything else is volatile He was like, "Whoa, I didn't think about that from that angle." That was eye-opener for him. he was like "whoa i didn't think about that from that angle." that was eye-opener for him He opened, like, work for our teams, and they've been delivering for him ever since. he opened like work for our teams and they've been delivering for him ever since Last but not least, I believe it's our results relentlessly attitude. last but not least i believe it's our results relentlessly attitude You know, London Stock Exchange, our huge client. you know london stock exchange our huge client They have a massive, like, program of migrating hundreds of applications from on-prem to Azure. they have a massive like program of migrating hundreds of applications from on-prem to azure By the way, like, several previous attempts failed with other vendors. by the way like several previous attempts failed with other vendors Just recently, we completed a first migration of the application that was done by a small Ukrainian team with a little bit of a sleepless nights, of course, with the usage of AI. just recently we completed a first migration of the application that was done by a small ukrainian team with a little bit of a sleepless nights of course with the usage of ai It was done on budget, on time, and client feedback was that it was the most seamless migration ever in his career. At the end of the day, while the environment may be volatile, we've proven that our delivery is a constant thing. We don't just meet the standard. I hope that we set the new one that could be called resilient partnership. It was done on budget, on time, and client feedback was that it was the most seamless migration ever in his career. it was done on budget on time and client feedback was that it was the most seamless migration ever in his career At the end of the day, while the environment may be volatile, we've proven that our delivery is a constant thing. at the end of the day while the environment may be volatile we've proven that our delivery is a constant thing We don't just meet the standard. we don't just meet the standard I hope that we set the new one that could be called resilient partnership. i hope that we set the new one that could be called resilient partnership

Speaker 4: No, it's absolutely. I mean, it's. I see this every time we having client conversation about Ukraine. As you said, if you wanna help Ukraine, work with us. Great. No, it's absolutely. no it's absolutely I mean, it's. i mean it's I see this every time we having client conversation about Ukraine. i see this every time we having client conversation about ukraine As you said, if you wanna help Ukraine, work with us. as you said if you wanna help ukraine work with us Great. great

Speaker 32: Thank you. Thank you. thank you

Speaker 4: Thank you, Stepan. Quick follow-up. One other interesting thing we saw in Ukraine was very early adoption of GenAI. In fact, some of the EPAM IP, like CodeMie and ELITEA, was born in Ukraine, which became part of EPAM AI/RUN platform. Again, what was sort of the driving force behind it? Thank you, Stepan. thank you stepan Quick follow-up. quick follow-up One other interesting thing we saw in Ukraine was very early adoption of GenAI. one other interesting thing we saw in ukraine was very early adoption of genai In fact, some of the EPAM IP, like CodeMie and ELITEA, was born in Ukraine, which became part of EPAM AI/RUN platform. in fact some of the epam ip like codemie and elitea was born in ukraine which became part of epam ai/run platform Again, what was sort of the driving force behind it? again what was sort of the driving force behind it

Speaker 32: Well, great question, Amit. In order to understand like how it happened, you have to understand Ukrainian engineering DNA. To be honest, we always been very fast adapters of everything new. Look at our Ministry of Digital Transformation, our Diia mobile app with the government in the mobile, with all the document services, defense tech, nearly cashless society. For us, like AI is not a hype, it's a kind of skin in the game. If we don't disrupt ourself, we're not gonna win. We're not gonna be successful in front of the clients. Yes, indeed, both tools, CodeMie and ELITEA, which are part of AI/RUN platform that Adam and Dima was talking about, was born in Ukraine and by Ukrainians, which basically proves that we not just like deliver despite all the adversities, but we also innovate. Well, great question, Amit. well great question amit In order to understand like how it happened, you have to understand Ukrainian engineering DNA. in order to understand like how it happened you have to understand ukrainian engineering dna To be honest, we always been very fast adapters of everything new. to be honest we always been very fast adapters of everything new Look at our Ministry of Digital Transformation, our Diia mobile app with the government in the mobile, with all the document services, defense tech, nearly cashless society. look at our ministry of digital transformation our diia mobile app with the government in the mobile with all the document services defense tech nearly cashless society For us, like AI is not a hype, it's a kind of skin in the game. for us like ai is not a hype it's a kind of skin in the game If we don't disrupt ourself, we're not gonna win. if we don't disrupt ourself we're not gonna win We're not gonna be successful in front of the clients. we're not gonna be successful in front of the clients Yes, indeed, both tools, CodeMie and ELITEA, which are part of AI/RUN platform that Adam and Dima was talking about, was born in Ukraine and by Ukrainians, which basically proves that we not just like deliver despite all the adversities, but we also innovate. yes indeed both tools codemie and elitea which are part of ai/run platform that adam and dima was talking about was born in ukraine and by ukrainians which basically proves that we not just like deliver despite all the adversities but we also innovate Yes, we see a shift in the engineering role from kind of how, which is code generation to a certain extent, to what and why which is focusing on complex, like client's challenges. Here is an example from real life. Vadim, who is a product manager of the CodeMie, it's an AI-native agentic platform. He was doing a demo, and during the demo app crashed. Instead of just panicking, he just like went to CodeMie agent and described the bug and asked agent to fix it, run the test, and deploy to production. We went for a 10-minute coffee break, returned back, and boom, it's already fixed and in production. Yes, we see a shift in the engineering role from kind of how, which is code generation to a certain extent, to what and why which is focusing on complex, like client's challenges. yes we see a shift in the engineering role from kind of how which is code generation to a certain extent to what and why which is focusing on complex like client's challenges Here is an example from real life. here is an example from real life Vadim, who is a product manager of the CodeMie, it's an AI-native agentic platform. vadim who is a product manager of the codemie it's an ai-native agentic platform He was doing a demo, and during the demo app crashed. he was doing a demo and during the demo app crashed Instead of just panicking, he just like went to CodeMie agent and described the bug and asked agent to fix it, run the test, and deploy to production. instead of just panicking he just like went to codemie agent and described the bug and asked agent to fix it run the test and deploy to production We went for a 10-minute coffee break, returned back, and boom, it's already fixed and in production. we went for a 10-minute coffee break returned back and boom it's already fixed and in production

Speaker 4: Like Boris from Anthropic said, Claude is coding Claude. Like Boris from Anthropic said, Claude is coding Claude. like boris from anthropic said claude is coding claude

Speaker 32: Exactly Exactly exactly

Speaker 4: CodeMie is coding code. CodeMie is coding code. codemie is coding code

Speaker 32: Exactly. Exactly. exactly

Speaker 4: It's amazing. Amazing story. It's amazing. it's amazing Amazing story. amazing story

Speaker 32: That is exactly the level of maturity we bring to our clients. It's not just about code snippets generation, it's about automations, the full cycle of software development. At the end of the day, we believe that AI is a multiplier for human brilliance. Given all the components we have and our strong engineering DNA, we believe that we're gonna remain steady, innovative partner that our client trust to continue solving their complex challenges. That is exactly the level of maturity we bring to our clients. that is exactly the level of maturity we bring to our clients It's not just about code snippets generation, it's about automations, the full cycle of software development. it's not just about code snippets generation it's about automations the full cycle of software development At the end of the day, we believe that AI is a multiplier for human brilliance. at the end of the day we believe that ai is a multiplier for human brilliance Given all the components we have and our strong engineering DNA, we believe that we're gonna remain steady, innovative partner that our client trust to continue solving their complex challenges. given all the components we have and our strong engineering dna we believe that we're gonna remain steady innovative partner that our client trust to continue solving their complex challenges

Speaker 4: That sounds amazing, Stepan. As you said, if you wanna win, you have to disrupt yourself first. That sounds amazing, Stepan. that sounds amazing stepan As you said, if you wanna win, you have to disrupt yourself first. as you said if you wanna win you have to disrupt yourself first

Speaker 32: Exactly. Exactly. exactly

Speaker 4: It's great. It's great. it's great

Speaker 32: Thank you. Thank you. thank you

Speaker 4: Srini. Srini. srini

Speaker 31: Yes, Amit. Yes, Amit. yes amit

Speaker 4: We should talk about India. We should talk about India. we should talk about india

Speaker 31: Yeah. Yeah. yeah

Speaker 4: Not about the pollution and traffic and the population, but EPAM India. Not about the pollution and traffic and the population, but EPAM India. not about the pollution and traffic and the population but epam india

Speaker 31: EPAM. EPAM. epam

Speaker 4: It became the largest location in EPAM in a span of what? 10 years or so, roughly? It became the largest location in EPAM in a span of what? 10 years or so, roughly? it became the largest location in epam in a span of what 10 years or so roughly

Speaker 31: That's right. That's right. that's right

Speaker 4: Clients tell us, and we see it ourselves, but clients tell us, which is probably a bigger proof point, that it's very different when they work with EPAM India versus the rest of the competition. What's behind the scenes story? How did you go about doing it? What's really different? Clients tell us, and we see it ourselves, but clients tell us, which is probably a bigger proof point, that it's very different when they work with EPAM India versus the rest of the competition. clients tell us and we see it ourselves but clients tell us which is probably a bigger proof point that it's very different when they work with epam india versus the rest of the competition What's behind the scenes story? what's behind the scenes story How did you go about doing it? how did you go about doing it What's really different? what's really different

Speaker 31: Thank you, Amit. I think we differentiated ourself in the India market by building a modern engineering company. It was built on our EPAM's global engineering culture and hiring quality talent. We did this over 10 years, and we did this very differently. Today I have very senior leadership teams in India that manage mature practices in cloud, in data, in data science, and now in AI and GenAI. Thank you, Amit. thank you amit I think we differentiated ourself in the India market by building a modern engineering company. i think we differentiated ourself in the india market by building a modern engineering company It was built on our EPAM's global engineering culture and hiring quality talent. it was built on our epam's global engineering culture and hiring quality talent We did this over 10 years, and we did this very differently. we did this over 10 years and we did this very differently Today I have very senior leadership teams in India that manage mature practices in cloud, in data, in data science, and now in AI and GenAI. today i have very senior leadership teams in india that manage mature practices in cloud in data in data science and now in ai and genai

Speaker 4: Local is strong leadership. Local is strong leadership. local is strong leadership

Speaker 31: Absolutely Absolutely absolutely

Speaker 4: is critical. is critical. is critical

Speaker 31: I remember the first global AI workshop was conducted in Hyderabad. This was for a week, more than 2.5 years ago. We have all our senior AI leaders in Hyderabad, and most of them are actually in this room today. When we were done, one of the OKRs that we came out was to make EPAM India the first AI-native location in EPAM. That, for us, really started with training our engineers. Today our AI literacy in EPAM India is 90%+. More than 70% of our projects leverage AI tooling, either our AI-run or some agentic AI that is provided by our client. In addition to that, the teams in India have also contributed to our AI initiatives. I remember the first global AI workshop was conducted in Hyderabad. i remember the first global ai workshop was conducted in hyderabad This was for a week, more than 2.5 years ago. this was for a week more than 2.5 years ago We have all our senior AI leaders in Hyderabad, and most of them are actually in this room today. we have all our senior ai leaders in hyderabad and most of them are actually in this room today When we were done, one of the OKRs that we came out was to make EPAM India the first AI-native location in EPAM. when we were done one of the okrs that we came out was to make epam india the first ai-native location in epam That, for us, really started with training our engineers. that for us really started with training our engineers Today our AI literacy in EPAM India is 90%+ . today our ai literacy in epam india is 90%+ More than 70% of our projects leverage AI tooling, either our AI-run or some agentic AI that is provided by our client. more than 70% of our projects leverage ai tooling either our ai-run or some agentic ai that is provided by our client In addition to that, the teams in India have also contributed to our AI initiatives. in addition to that the teams in india have also contributed to our ai initiatives We built the AIOps platform that we leverage on all our managed services engagements. We built the AIOps platform that we leverage on all our managed services engagements. we built the aiops platform that we leverage on all our managed services engagements

Speaker 4: Which is now part of EPAM AI/RUN bigger platform. Which is now part of EPAM AI/RUN bigger platform. which is now part of epam ai/run bigger platform

Speaker 31: That's right. That's right. that's right

Speaker 4: umbrella. umbrella. umbrella

Speaker 31: That's right. That's right. that's right

Speaker 4: Yeah. Yeah. yeah

Speaker 31: We also built an AI reverse engineering tool and agentic swarms for use on our modernization projects, right? If you think about it, some of EPAM's largest implementation on CodeMie, on ELITEA, on Claude Code, are being run out of programs in India today. We also built an AI reverse engineering tool and agentic swarms for use on our modernization projects, right? we also built an ai reverse engineering tool and agentic swarms for use on our modernization projects right If you think about it, some of EPAM's largest implementation on CodeMie, on ELITEA, on Claude Code, are being run out of programs in India today. if you think about it some of epam's largest implementation on codemie on elitea on claude code are being run out of programs in india today

Speaker 4: Yeah. No, we see that. We see AI adoption at scale with large enterprise in India, so well done. Thank you, Srinivas. Yeah. yeah No, we see that. no we see that We see AI adoption at scale with large enterprise in India, so well done. we see ai adoption at scale with large enterprise in india so well done Thank you, Srinivas. thank you srinivas

Speaker 31: Thank you. Thank you. thank you

Speaker 4: Quick follow-up. Quick follow-up. quick follow-up

Speaker 31: Yeah. Yeah. yeah

Speaker 4: Again, being the largest location, you play a very big role in EPAM's geographic diversification for U.S. customers, European customers all over the world. You have the other side of the coin as well, which is GCCs, which are rapidly coming up and building in India. Could you talk a little bit about it? Do you think GCC is a big opportunity for EPAM? Again, being the largest location, you play a very big role in EPAM's geographic diversification for U.S. customers, European customers all over the world. again being the largest location you play a very big role in epam's geographic diversification for u.s customers european customers all over the world You have the other side of the coin as well, which is GCCs, which are rapidly coming up and building in India. you have the other side of the coin as well which is gccs which are rapidly coming up and building in india Could you talk a little bit about it? could you talk a little bit about it Do you think GCC is a big opportunity for EPAM? do you think gcc is a big opportunity for epam

Speaker 31: Yeah, a good question, Amit. As you're aware, we today work with 150+ clients in India, and we work with them in various different delivery models. The traditional outsourcing where the teams are exclusively based in India and hybrid, and we do quite a bit of work today in the hybrid model where we have teams in India, but we also have teams in one or multiple of the other locations. And like you said, in the local market, we work with those global capability centers or GCCs. Today, we work with somewhere between 50-60 GCCs in India, and we've been working with them for more than 10 years. And over those 10 years we've built strong local relationships and today, I think in most of them we are their trusted partner. Yeah, a good question, Amit. yeah a good question amit As you're aware, we today work with 150+ clients in India, and we work with them in various different delivery models. as you're aware we today work with 150+ clients in india and we work with them in various different delivery models The traditional outsourcing where the teams are exclusively based in India and hybrid, and we do quite a bit of work today in the hybrid model where we have teams in India, but we also have teams in one or multiple of the other locations. the traditional outsourcing where the teams are exclusively based in india and hybrid and we do quite a bit of work today in the hybrid model where we have teams in india but we also have teams in one or multiple of the other locations And like you said, in the local market, we work with those global capability centers or GCCs. and like you said in the local market we work with those global capability centers or gccs Today, we work with somewhere between 50-60 GCCs in India, and we've been working with them for more than 10 years. today we work with somewhere between 50-60 gccs in india and we've been working with them for more than 10 years And over those 10 years we've built strong local relationships and today, I think in most of them we are their trusted partner. and over those 10 years we've built strong local relationships and today i think in most of them we are their trusted partner I think that's happened mostly because of our advanced engineering skills, our AI capabilities, which really complements what the GCCs themselves are looking to build in India. The answer to your question is yes, Amit. I think their rapid growth over the last few years in India is actually an opportunity for us. I think that's happened mostly because of our advanced engineering skills, our AI capabilities, which really complements what the GCCs themselves are looking to build in India. i think that's happened mostly because of our advanced engineering skills our ai capabilities which really complements what the gccs themselves are looking to build in india The answer to your question is yes, Amit. the answer to your question is yes amit I think their rapid growth over the last few years in India is actually an opportunity for us. i think their rapid growth over the last few years in india is actually an opportunity for us

Speaker 4: Premium skills and proximity to GCC is. Premium skills and proximity to GCC is. premium skills and proximity to gcc is

Speaker 31: That's right. That's right. that's right

Speaker 4: is what they're looking for, and- is what they're looking for, and- is what they're looking for and-

Speaker 31: Yeah Yeah yeah

Speaker 4: sounds like we're winning there. sounds like we're winning there. sounds like we're winning there

Speaker 31: Yeah. Yeah. yeah

Speaker 4: No pressure. No pressure. no pressure

Speaker 31: Thank you. Thank you. thank you

Speaker 4: Okay. Before we wrap up, there is one big question we have to sort of talk about, which is we see, and the industry is talking a lot about it, there are a lot of large complex enterprise clients are stuck in this R&D and POC phase and not really able to scale GenAI into their environment. We have seen some early success with these organizations, so can I ask both you and Martin to share some examples where you believe that we managed to unlock the key? Okay. okay Before we wrap up, there is one big question we have to sort of talk about, which is we see, and the industry is talking a lot about it, there are a lot of large complex enterprise clients are stuck in this R&D and POC phase and not really able to scale GenAI into their environment. before we wrap up there is one big question we have to sort of talk about which is we see and the industry is talking a lot about it there are a lot of large complex enterprise clients are stuck in this r&d and poc phase and not really able to scale genai into their environment We have seen some early success with these organizations, so can I ask both you and Martin to share some examples where you believe that we managed to unlock the key? we have seen some early success with these organizations so can i ask both you and martin to share some examples where you believe that we managed to unlock the key

Speaker 13: With pleasure. With pleasure. with pleasure

Speaker 23: Yeah. Yeah. yeah

Speaker 13: Martin, would you like me to start? Martin, would you like me to start? martin would you like me to start

Speaker 23: Okay. Okay. okay

Speaker 13: Okay. Yeah, indeed. Clients are quite excited and to certain extent under pressure, as you rightly said, and they run multiple POCs in the last couple of years, and now they really get to see real implementations with real returns of the investments. I believe opportunity is big and EPAM is very well positioned to capture it. The key arguments for this are, as you all heard, our top-notch technology excellence. Second is industry knowledge accumulated over the years, and third is our early and very practical investment into AI. All of this helped us to form very concrete industry aligned points of view on how AI and modern platforms can transform our clients' businesses. Importantly, we didn't stay on PowerPoint levels. Okay. okay Yeah, indeed. yeah indeed Clients are quite excited and to certain extent under pressure, as you rightly said, and they run multiple POCs in the last couple of years, and now they really get to see real implementations with real returns of the investments. clients are quite excited and to certain extent under pressure as you rightly said and they run multiple pocs in the last couple of years and now they really get to see real implementations with real returns of the investments I believe opportunity is big and EPAM is very well positioned to capture it. i believe opportunity is big and epam is very well positioned to capture it The key arguments for this are, as you all heard, our top-notch technology excellence. the key arguments for this are as you all heard our top-notch technology excellence Second is industry knowledge accumulated over the years, and third is our early and very practical investment into AI. second is industry knowledge accumulated over the years and third is our early and very practical investment into ai All of this helped us to form very concrete industry aligned points of view on how AI and modern platforms can transform our clients' businesses. all of this helped us to form very concrete industry aligned points of view on how ai and modern platforms can transform our clients' businesses Importantly, we didn't stay on PowerPoint levels. importantly we didn't stay on powerpoint levels We went all the way and implemented industry specific accelerators and our clients use it nowadays. Just to give you a couple of examples. First one was Swiss Re. They used to produce sigma report, very well known in the industry. We helped Swiss Re to ideate, validate and deliver Sigma Explorer, something that connects all resources, all publications, all data sets, and helps end users to talk to the data, do the data analytics using the natural language. We developed the system using two EPAM accelerators, DIAL and QuantHub, and it went live in a very short period of time. Another very important example is gonna be 1&1 or how they call it in Germany, 1&1, major German telco. We went all the way and implemented industry specific accelerators and our clients use it nowadays. we went all the way and implemented industry specific accelerators and our clients use it nowadays Just to give you a couple of examples. just to give you a couple of examples First one was Swiss Re. first one was swiss re They used to produce sigma report, very well known in the industry. they used to produce sigma report very well known in the industry We helped Swiss Re to ideate, validate and deliver Sigma Explorer, something that connects all resources, all publications, all data sets, and helps end users to talk to the data, do the data analytics using the natural language. we helped swiss re to ideate validate and deliver sigma explorer something that connects all resources all publications all data sets and helps end users to talk to the data do the data analytics using the natural language We developed the system using two EPAM accelerators, DIAL and QuantHub, and it went live in a very short period of time. we developed the system using two epam accelerators dial and quanthub and it went live in a very short period of time Another very important example is gonna be 1&1 or how they call it in Germany, 1&1, major German telco. another very important example is gonna be 1&1 or how they call it in germany 1&1 major german telco They wanted to reimagine the way how they interact with their users. We developed for them an agentic AI platform that today handles hundreds of thousands of end user calls. Not only helped to cut operational costs, but it improved the client satisfaction level. We used our AI/RUN transform platform to develop it, and the first agents went live just within several months. They wanted to reimagine the way how they interact with their users. they wanted to reimagine the way how they interact with their users We developed for them an agentic AI platform that today handles hundreds of thousands of end user calls. we developed for them an agentic ai platform that today handles hundreds of thousands of end user calls Not only helped to cut operational costs, but it improved the client satisfaction level. not only helped to cut operational costs but it improved the client satisfaction level We used our AI/RUN transform platform to develop it, and the first agents went live just within several months. we used our ai/run transform platform to develop it and the first agents went live just within several months

Speaker 4: Sounds like we need to say good luck to our friends who are running traditional BPO industry. Sounds like we need to say good luck to our friends who are running traditional BPO industry. sounds like we need to say good luck to our friends who are running traditional bpo industry

Speaker 13: I will do this. I will do this. i will do this

Speaker 4: Okay. Martin? Okay. okay Martin? martin

Speaker 23: I have three examples of Latin America, and this is in Latin America. One is, there's a large utility company in Brazil that is doing a big migration from a legacy system into SAP on the cloud, and there is a big need to migrate tons of data. At the same time, they are going through an M&A strategy towards acquiring companies in the region. They were thinking about how to do it. We were competing with some of the local competitors, and they were going for more the traditional approach of migrating data. We came with AI/RUN and migVisor as one of the platforms that we have. I have three examples of Latin America, and this is in Latin America. i have three examples of latin america and this is in latin america One is, there's a large utility company in Brazil that is doing a big migration from a legacy system into SAP on the cloud, and there is a big need to migrate tons of data. one is there's a large utility company in brazil that is doing a big migration from a legacy system into sap on the cloud and there is a big need to migrate tons of data At the same time, they are going through an M&A strategy towards acquiring companies in the region. at the same time they are going through an m&a strategy towards acquiring companies in the region They were thinking about how to do it. they were thinking about how to do it We were competing with some of the local competitors, and they were going for more the traditional approach of migrating data. we were competing with some of the local competitors and they were going for more the traditional approach of migrating data We came with AI/RUN and migVisor as one of the platforms that we have. we came with ai/run and migvisor as one of the platforms that we have We've been able to prove them that by using this platform, we are gonna be not just able to do it faster in the first time, but also have a repeatable agent that will help later in the future acquisition. That's one of the first cases, and it's very interesting. The second one is like we have a large manufacturing company in Latin America where it's having like cameras to surveillance the plants. We've been able to prove them that by using this platform, we are gonna be not just able to do it faster in the first time, but also have a repeatable agent that will help later in the future acquisition. we've been able to prove them that by using this platform we are gonna be not just able to do it faster in the first time but also have a repeatable agent that will help later in the future acquisition That's one of the first cases, and it's very interesting. that's one of the first cases and it's very interesting The second one is like we have a large manufacturing company in Latin America where it's having like cameras to surveillance the plants. the second one is like we have a large manufacturing company in latin america where it's having like cameras to surveillance the plants

Speaker 4: Not for spying. Not for spying. not for spying

Speaker 23: Eh? Eh? eh

Speaker 4: Not for spying. Not for spying. not for spying

Speaker 23: Not for spying, but at the end, we transform those cameras into a living agent that is serving what's going on. Now we are able to track all the tractor into the plant and foresee what they are doing and optimize their routes. We're also monitoring inventories, and we are helping them with health and safety in terms of seeing if the people are in the right places, they are using their helmets and the like. That was a physical platform that was there without taking the value. Not for spying, but at the end, we transform those cameras into a living agent that is serving what's going on. not for spying but at the end we transform those cameras into a living agent that is serving what's going on Now we are able to track all the tractor into the plant and foresee what they are doing and optimize their routes. now we are able to track all the tractor into the plant and foresee what they are doing and optimize their routes We're also monitoring inventories, and we are helping them with health and safety in terms of seeing if the people are in the right places, they are using their helmets and the like. we're also monitoring inventories and we are helping them with health and safety in terms of seeing if the people are in the right places they are using their helmets and the like That was a physical platform that was there without taking the value. that was a physical platform that was there without taking the value We explore that. Last but not least, in terms of agentic, we also implemented an agentic platform in one of our customers that is in the bakery industry to help them to better serve their suppliers and give them information of where their payments were, if there was something that it was blocking, when to expect those payments to happen. That allows them to reduce like 30% of their physical agents and it's kind of case of the BPO that you werehey were mentioning. We explore that. we explore that Last but not least, in terms of agentic, we also implemented an agentic platform in one of our customers that is in the bakery industry to help them to better serve their suppliers and give them information of where their payments were, if there was something that it was blocking, when to expect those payments to happen. last but not least in terms of agentic we also implemented an agentic platform in one of our customers that is in the bakery industry to help them to better serve their suppliers and give them information of where their payments were if there was something that it was blocking when to expect those payments to happen That allows them to reduce like 30% of their physical agents and it's kind of case of the BPO that you were hey were mentioning. that allows them to reduce like 30% of their physical agents and it's kind of case of the bpo that you were hey were mentioning

Speaker 4: I think sounds like based on examples both of you said is it's a combination of industry depth, good old EPAM engineering, but applied in a forward deployed capacity to work with clients closely. That's great. Thank you. Thank you. I think sounds like based on examples both of you said is it's a combination of industry depth, good old EPAM engineering, but applied in a forward deployed capacity to work with clients closely. i think sounds like based on examples both of you said is it's a combination of industry depth good old epam engineering but applied in a forward deployed capacity to work with clients closely That's great. that's great Thank you. thank you Thank you. thank you

Speaker 13: Thank you. Thank you. thank you

Speaker 32: Thank you, Amit. Thank you, Amit. thank you amit

Speaker 4: Martin and Enver for sharing cool examples. Thank you Srini and Stepaan for what you do. Martin and Enver for sharing cool examples. martin and enver for sharing cool examples Thank you Srini and Stepaan for what you do. thank you srini and stepaan for what you do

Speaker 32: Thank you. Thank you. thank you

Speaker 4: How you do. Between two of you, we have good part of EPAM, so no pressure again. Sounds like resilience by design. We need more of it. Thank you all, and that's a wrap. How you do. how you do Between two of you, we have good part of EPAM, so no pressure again. between two of you we have good part of epam so no pressure again Sounds like resilience by design. sounds like resilience by design We need more of it. we need more of it Thank you all, and that's a wrap. thank you all and that's a wrap

Speaker 32: Thank you. Thank you. thank you

Speaker 4: Next you're gonna hear from our CFO, Jason Peterson. Before Jason comes on the stage, again, let's hear from one of the EPAM clients. They're called Louis Dreyfus Company, one of the largest global commodity trading, soft commodity trading company and logistics company. Enjoy the video, and then you'll hear from Jason. Thank you. Next you're gonna hear from our CFO, Jason Peterson. next you're gonna hear from our cfo jason peterson Before Jason comes on the stage, again, let's hear from one of the EPAM clients. before jason comes on the stage again let's hear from one of the epam clients They're called Louis Dreyfus Company, one of the largest global commodity trading, soft commodity trading company and logistics company. they're called louis dreyfus company one of the largest global commodity trading soft commodity trading company and logistics company Enjoy the video, and then you'll hear from Jason. enjoy the video and then you'll hear from jason Thank you. thank you

Speaker 14: It's great to be here with you today. I'm Guy-Laurent Arpino, and I serve as Chief Information Officer at Louis Dreyfus Company or LDC, which is one of the world's leading global merchants and processors of agricultural goods since 1851. I oversee our global digital strategy and technology initiatives spanning trading, supply chains, and corporate functions. I've been part of LDC for 10 years, following 15 years at Procter & Gamble and 5 years at Bacardi. We began working with EPAM in 2019 on our analytics and BI transformation, quickly scaling teams across Hungary and Belarus. The partnership expanded naturally into software engineering with projects such as My LDC, our customer portal, and our largest front office program. Throughout COVID and various geopolitical disruptions, EPAM has ensured delivery continuity and helped us scale effectively. It's great to be here with you today. it's great to be here with you today I'm Guy-Laurent Arpino, and I serve as Chief Information Officer at Louis Dreyfus Company or LDC, which is one of the world's leading global merchants and processors of agricultural goods since 1851. i'm guy-laurent arpino and i serve as chief information officer at louis dreyfus company or ldc which is one of the world's leading global merchants and processors of agricultural goods since 1851 I oversee our global digital strategy and technology initiatives spanning trading, supply chains, and corporate functions. i oversee our global digital strategy and technology initiatives spanning trading supply chains and corporate functions I've been part of LDC for 10 years, following 15 years at Procter & Gamble and 5 years at Bacardi. i've been part of ldc for 10 years following 15 years at procter & gamble and 5 years at bacardi We began working with EPAM in 2019 on our analytics and BI transformation, quickly scaling teams across Hungary and Belarus. we began working with epam in 2019 on our analytics and bi transformation quickly scaling teams across hungary and belarus The partnership expanded naturally into software engineering with projects such as My LDC, our customer portal, and our largest front office program. the partnership expanded naturally into software engineering with projects such as my ldc our customer portal and our largest front office program Throughout COVID and various geopolitical disruptions, EPAM has ensured delivery continuity and helped us scale effectively. throughout covid and various geopolitical disruptions epam has ensured delivery continuity and helped us scale effectively They also executed the award-winning migration of our five global data centers to Microsoft Azure in just 24 months. More recently, we've partnered on strategic AI initiatives, including next generation pricing engines. What truly differentiates the relationship is our shared focus, not only on what we built but how we built it, ensuring scalable, sustainable, and modern engineering practices in a fast-evolving landscape. Today, we jointly embark on fully leveraging the potential of agentic AI software development life cycle, transforming the way IT solutions are being designed, implemented, and delivered at scale. This will allow us to achieve our ambitious roadmap to become an AI-powered company. Over the years, EPAM has played a significant role in modernizing the application landscape, enhancing our enterprise architecture, and reducing technical debt by approximately 40%. They also executed the award-winning migration of our five g lobal data centers to Microsoft Azure in just 24 months. they also executed the award-winning migration of our five g lobal data centers to microsoft azure in just 24 months More recently, we've partnered on strategic AI initiatives, including next generation pricing engines. more recently we've partnered on strategic ai initiatives including next generation pricing engines What truly differentiates the relationship is our shared focus, not only on what we built but how we built it, ensuring scalable, sustainable, and modern engineering practices in a fast-evolving landscape. what truly differentiates the relationship is our shared focus not only on what we built but how we built it ensuring scalable sustainable and modern engineering practices in a fast-evolving landscape Today, we jointly embark on fully leveraging the potential of agentic AI software development life cycle, transforming the way IT solutions are being designed, implemented, and delivered at scale. today we jointly embark on fully leveraging the potential of agentic ai software development life cycle transforming the way it solutions are being designed implemented and delivered at scale This will allow us to achieve our ambitious roadmap to become an AI-powered company. this will allow us to achieve our ambitious roadmap to become an ai-powered company Over the years, EPAM has played a significant role in modernizing the application landscape, enhancing our enterprise architecture, and reducing technical debt by approximately 40%. over the years epam has played a significant role in modernizing the application landscape enhancing our enterprise architecture and reducing technical debt by approximately 40% In addition, we've made substantial progress in our data estate, developing a data platform on Microsoft Azure from the ground up. This platform serves as the cornerstone for both our data and science initiatives and AI-based products and services. We anticipate further opportunities for collaboration and innovation and AI-enabled software development. I can only advise you to keep the high degree of ownership and accountability in the delivery of our projects, and I look forward to benefiting from the broader perspective across industries and the technological landscape, particularly around AI. In addition, we've made substantial progress in our data estate, developing a data platform on Microsoft Azure from the ground up. in addition we've made substantial progress in our data estate developing a data platform on microsoft azure from the ground up This platform serves as the cornerstone for both our data and science initiatives and AI-based products and services. this platform serves as the cornerstone for both our data and science initiatives and ai-based products and services We anticipate further opportunities for collaboration and innovation and AI-enabled software development. we anticipate further opportunities for collaboration and innovation and ai-enabled software development I can only advise you to keep the high degree of ownership and accountability in the delivery of our projects, and I look forward to benefiting from the broader perspective across industries and the technological landscape, particularly around AI. i can only advise you to keep the high degree of ownership and accountability in the delivery of our projects and i look forward to benefiting from the broader perspective across industries and the technological landscape particularly around ai

Speaker 18: In this final presentation of the day before EPAM's closing remarks, it's probably gonna be no surprise that I'm gonna talk about the business from more of a financial perspective. I'm also gonna lay out our expectations for the coming three years, 2026, 2027, and 2028. I'm gonna focus on our accelerating revenue growth. I'm also gonna talk about our improving profitability, and then I'm gonna talk about our ability to continue to generate strong free cash flows. First, I wanna explain kind of what's in this slide. Off to the left, clearly it's 2022 through 2025 are actuals. For 2026, what I'm showing you is just the midpoint of the guided range from our most recent February earnings call. In this final presentation of the day before EPAM's closing remarks, it's probably gonna be no surprise that I'm gonna talk about the business from more of a financial perspective. in this final presentation of the day before epam's closing remarks it's probably gonna be no surprise that i'm gonna talk about the business from more of a financial perspective I'm also gonna lay out our expectations for the coming three years, 2026, 2027, and 2028. i'm also gonna lay out our expectations for the coming three years 2026 2027 and 2028 I'm gonna focus on our accelerating revenue growth. i'm gonna focus on our accelerating revenue growth I'm also gonna talk about our improving profitability, and then I'm gonna talk about our ability to continue to generate strong free cash flows. i'm also gonna talk about our improving profitability and then i'm gonna talk about our ability to continue to generate strong free cash flows First, I wanna explain kind of what's in this slide. first i wanna explain kind of what's in this slide Off to the left, clearly it's 2022 through 2025 are actuals. off to the left clearly it's 2022 through 2025 are actuals For 2026, what I'm showing you is just the midpoint of the guided range from our most recent February earnings call. for 2026 what i'm showing you is just the midpoint of the guided range from our most recent february earnings call You know, I think the point that I wanna make, and I think Larry did a really good job of kind of reminding us kind of what we've been through over the last four to five years, is that, you know, we had to deal with increasing sort of difficulty in our operations in Belarus. We had the invasion of Ukraine. We exited Russia. That was both a delivery location, and it was also a revenue generation, revenue-generating market for the company. We were able to maintain steady revenues throughout this time period, returning to growth at the end of 2024. Further improving our growth rate in 2025, where we recently discussed our organic constant currency growth rate of approximately 5%. More recently, discussed our expectations for 2026 with a 3%-6% organic constant currency growth rate. You know, I think the point that I wanna make, and I think Larry did a really good job of kind of reminding us kind of what we've been through over the last four to five years, is that, you know, we had to deal with increasing sort of difficulty in our operations in Belarus. you know i think the point that i wanna make and i think larry did a really good job of kind of reminding us kind of what we've been through over the last four to five years is that you know we had to deal with increasing sort of difficulty in our operations in belarus We had the invasion of Ukraine. we had the invasion of ukraine We exited Russia. we exited russia That was both a delivery location, and it was also a revenue generation, revenue-generating market for the company. that was both a delivery location and it was also a revenue generation revenue-generating market for the company We were able to maintain steady revenues throughout this time period, returning to growth at the end of 2024. we were able to maintain steady revenues throughout this time period returning to growth at the end of 2024 Further improving our growth rate in 2025, where we recently discussed our organic constant currency growth rate of approximately 5%. further improving our growth rate in 2025 where we recently discussed our organic constant currency growth rate of approximately 5% More recently, discussed our expectations for 2026 with a 3%-6% organic constant currency growth rate. more recently discussed our expectations for 2026 with a 3%-6% organic constant currency growth rate If I look over to the profitability side, from a non-GAAP operating income standpoint, you know, we're nothing if not adaptable. Again, what we've been through with having to move our populations, support our employees, make certain that we've maintained our customer commitments, continue to invest significantly in capabilities, particularly all the AI capabilities we've been talking about. We're able to maintain sort of steady non-GAAP operating income throughout the time period, again returning to growth in 2024, further accelerating that growth in 2025. We're talking about solid growth as we move from 2025 to 2026. Off to the far right with the non-GAAP diluted EPS, again, you've had growth throughout the last three years. For 2026, including the share repurchases, we actually return to double-digit growth in non-GAAP EPS between 2025 and 2026. If I look over to the profitability side, from a non-GAAP operating income standpoint, you know, we're nothing if not adaptable. if i look over to the profitability side from a non-gaap operating income standpoint you know we're nothing if not adaptable Again, what we've been through with having to move our populations, support our employees, make certain that we've maintained our customer commitments, continue to invest significantly in capabilities, particularly all the AI capabilities we've been talking about. again what we've been through with having to move our populations support our employees make certain that we've maintained our customer commitments continue to invest significantly in capabilities particularly all the ai capabilities we've been talking about We're able to maintain sort of steady non-GAAP operating income throughout the time period, again returning to growth in 2024, further accelerating that growth in 2025. we're able to maintain sort of steady non-gaap operating income throughout the time period again returning to growth in 2024 further accelerating that growth in 2025 We're talking about solid growth as we move from 2025 to 2026. we're talking about solid growth as we move from 2025 to 2026 Off to the far right with the non-GAAP diluted EPS, again, you've had growth throughout the last three years. off to the far right with the non-gaap diluted eps again you've had growth throughout the last three years For 2026, including the share repurchases, we actually return to double-digit growth in non-GAAP EPS between 2025 and 2026. for 2026 including the share repurchases we actually return to double-digit growth in non-gaap eps between 2025 and 2026 I think this is a really interesting, and you've seen this kinda throughout the day. Why it's interesting to me is that not only is our expanded geographic footprint a source of revenue growth for the company, but it's also an opportunity for us to continue to expand profitability. I think we've talked about the fact that, you know, we really have delivery excellence regardless of geography. We've got AI capabilities globally in all of the regions in which we operate. You know, what we'd understand then is that, of course, now instead of just delivering from Belarus, Ukraine, and Russia, we now have the opportunity to deliver around the globe. We can meet client expectations for different time zones, different price points, and when clients have specific sort of preferences in terms of geography. I think this is a really interesting, and you've seen this kinda throughout the day. i think this is a really interesting and you've seen this kinda throughout the day Why it's interesting to me is that not only is our expanded geographic footprint a source of revenue growth for the company, but it's also an opportunity for us to continue to expand profitability. why it's interesting to me is that not only is our expanded geographic footprint a source of revenue growth for the company but it's also an opportunity for us to continue to expand profitability I think we've talked about the fact that, you know, we really have delivery excellence regardless of geography. i think we've talked about the fact that you know we really have delivery excellence regardless of geography We've got AI capabilities globally in all of the regions in which we operate. we've got ai capabilities globally in all of the regions in which we operate You know, what we'd understand then is that, of course, now instead of just delivering from Belarus, Ukraine, and Russia, we now have the opportunity to deliver around the globe. you know what we'd understand then is that of course now instead of just delivering from belarus ukraine and russia we now have the opportunity to deliver around the globe We can meet client expectations for different time zones, different price points, and when clients have specific sort of preferences in terms of geography. we can meet client expectations for different time zones different price points and when clients have specific sort of preferences in terms of geography Now on top of that, let's talk about profitability. You know, I think what everyone would understand is when the invasion of Ukraine happened, the exit from Russia, we had to move quickly. We had to move into new countries. We had to grow rapidly. Okay. The net result was that we were taking care of our employees. We're meeting our client expectations for delivery. At the same time, we were growing and then obviously focused on cost efficiency, but it was a lower priority. Okay. Today, we've been much more focused on cost efficiency in some of the newer geographies and the geographies that scaled quickly. Now on top of that, let's talk about profitability. now on top of that let's talk about profitability You know, I think what everyone would understand is when the invasion of Ukraine happened, the exit from Russia, we had to move quickly. you know i think what everyone would understand is when the invasion of ukraine happened the exit from russia we had to move quickly We had to move into new countries. we had to move into new countries We had to grow rapidly. we had to grow rapidly Okay. okay The net result was that we were taking care of our employees. the net result was that we were taking care of our employees We're meeting our client expectations for delivery. we're meeting our client expectations for delivery At the same time, we were growing and then obviously focused on cost efficiency, but it was a lower priority. at the same time we were growing and then obviously focused on cost efficiency but it was a lower priority Okay. okay Today, we've been much more focused on cost efficiency in some of the newer geographies and the geographies that scaled quickly. today we've been much more focused on cost efficiency in some of the newer geographies and the geographies that scaled quickly I think I've been saying for the last couple years that, you know, even if you're worried about bill rates in India, we can still maintain high levels of profitability there and that India actually generates higher profitability than the company average. If you add to that the fact that we've been focused on the cost efficiency, India continues to improve profitability, and the gap between India profitability and EPAM average profitability continues to grow. We've done similar things in Western Central Asia, where we've continued to grow our profitability. LatAm has been interesting because, you know, one of the advantages of the Neoris acquisition is we've learned a lot more about how to operate efficiently in Colombia and more recently in Argentina. In all these cases, this gives us a further opportunity to sort of improve our profitability. I think I've been saying for the last couple years that, you know, even if you're worried about bill rates in India, we can still maintain high levels of profitability there and that India actually generates higher profitability than the company average. i think i've been saying for the last couple years that you know even if you're worried about bill rates in india we can still maintain high levels of profitability there and that india actually generates higher profitability than the company average If you add to that the fact that we've been focused on the cost efficiency, India continues to improve profitability, and the gap between India profitability and EPAM average profitability continues to grow. if you add to that the fact that we've been focused on the cost efficiency india continues to improve profitability and the gap between india profitability and epam average profitability continues to grow We've done similar things in Western Central Asia, where we've continued to grow our profitability. we've done similar things in western central asia where we've continued to grow our profitability LatAm has been interesting because, you know, one of the advantages of the Neoris acquisition is we've learned a lot more about how to operate efficiently in Colombia and more recently in Argentina. latam has been interesting because you know one of the advantages of the neoris acquisition is we've learned a lot more about how to operate efficiently in colombia and more recently in argentina In all these cases, this gives us a further opportunity to sort of improve our profitability. in all these cases this gives us a further opportunity to sort of improve our profitability It's one of the reasons why we're guiding towards profitable revenue growth in 2026 with an expansion in gross margin. This is effectively just a reiteration of guidance, right? It's $1.385 billion-$1.4 billion for Q1. For the full year, 4.5%-7.5%, which digests down to 3%-6% organic constant currency growth. What you'll note for the non-GAAP income from operations measured as a percent of revenue is that the 13.5%-14.5% for Q1, okay, at the midpoint is higher than what we generated in Q1 of 2025. The same thing's true for the full year 2026. The midpoint of the 15%-16% range, again, higher than what we actually produced in 2025. We're seeing not only revenue growth, but improving profitability. It's one of the reasons why we're guiding towards profitable revenue growth in 2026 with an expansion in gross margin. it's one of the reasons why we're guiding towards profitable revenue growth in 2026 with an expansion in gross margin This is effectively just a reiteration of guidance, right? this is effectively just a reiteration of guidance right It's $1.385 billion-$1.4 billion for Q1. it's $1.385 billion-$1.4 billion for q1 For the full year, 4.5%-7.5%, which digests down to 3%-6% organic constant currency growth. for the full year 4.5%-7.5% which digests down to 3%-6% organic constant currency growth What you'll note for the non-GAAP income from operations measured as a percent of revenue is that the 13.5%-14.5% for Q1, okay, at the midpoint is higher than what we generated in Q1 of 2025. what you'll note for the non-gaap income from operations measured as a percent of revenue is that the 13.5%-14.5% for q1 okay at the midpoint is higher than what we generated in q1 of 2025 The same thing's true for the full year 2026. the same thing's true for the full year 2026 The midpoint of the 15%-16% range, again, higher than what we actually produced in 2025. the midpoint of the 15%-16% range again higher than what we actually produced in 2025 We're seeing not only revenue growth, but improving profitability. we're seeing not only revenue growth but improving profitability Again, you go to the bottom portion of this page here, and you add the addition of the share repurchases, and you've got double-digit growth in non-GAAP diluted EPS, approximately 14% in Q1 and at the midpoint of the range, approximately 11% for the full year. From a long-term financial algorithm, you know, what you're really looking at is a focus on continuing to grow and to accelerate that growth through success in the market for AI native and AI foundational services. We're looking to continue to expand profitability. Again, that'll be with a focus on sort of cost efficiency. We've all talked about AI productivity and the opportunity to share those benefits with clients, give them some cost efficiency, retain some for ourselves, which improves gross margin. Again, you go to the bottom portion of this page here, and you add the addition of the share repurchases, and you've got double-digit growth in non-GAAP diluted EPS, approximately 14% in Q1 and at the midpoint of the range, approximately 11% for the full year. again you go to the bottom portion of this page here and you add the addition of the share repurchases and you've got double-digit growth in non-gaap diluted eps approximately 14% in q1 and at the midpoint of the range approximately 11% for the full year From a long-term financial algorithm, you know, what you're really looking at is a focus on continuing to grow and to accelerate that growth through success in the market for AI native and AI foundational services. from a long-term financial algorithm you know what you're really looking at is a focus on continuing to grow and to accelerate that growth through success in the market for ai native and ai foundational services We're looking to continue to expand profitability. we're looking to continue to expand profitability Again, that'll be with a focus on sort of cost efficiency. again that'll be with a focus on sort of cost efficiency We've all talked about AI productivity and the opportunity to share those benefits with clients, give them some cost efficiency, retain some for ourselves, which improves gross margin. we've all talked about ai productivity and the opportunity to share those benefits with clients give them some cost efficiency retain some for ourselves which improves gross margin We've always had strong operating cash flows, modest capital expenditures, so that produces strong free cash flow. From a capital allocation standpoint, we continue to invest in our business, we've done strategic M&A, and more recently, we've introduced share repurchases, including the $300 million ASR that was announced in March of this year. From a growth standpoint, I think, you know, what I'd first do is take you off to the right side of the page. You know, we are participating in an immense $1.8 trillion IT services market. Again, we're quoting the Gartner statistics. That market is growing. We've always had strong operating cash flows, modest capital expenditures, so that produces strong free cash flow. we've always had strong operating cash flows modest capital expenditures so that produces strong free cash flow From a capital allocation standpoint, we continue to invest in our business, we've done strategic M&A, and more recently, we've introduced share repurchases, including the $300 million ASR that was announced in March of this year. from a capital allocation standpoint we continue to invest in our business we've done strategic m&a and more recently we've introduced share repurchases including the $300 million asr that was announced in march of this year From a growth standpoint, I think, you know, what I'd first do is take you off to the right side of the page. from a growth standpoint i think you know what i'd first do is take you off to the right side of the page You know, we are participating in an immense $1.8 trillion IT services market. you know we are participating in an immense $1.8 trillion it services market Again, we're quoting the Gartner statistics. again we're quoting the gartner statistics That market is growing. that market is growing Underneath or within that market, there's the much higher growth opportunities associated with AI native, AI foundational, and then we've talked off and on throughout the day about kind of the more greenfield opportunities for EPAM, agentic BPO, AI-enabled managed services. There'll probably be some contribution from M&A over time. What we are looking to do is continue to accelerate our revenue growth by participating and, more importantly, succeeding in the high-growth markets. With a goal of eventually returning to 10% or a double-digit organic constant currency revenue growth. From a profitability standpoint, you know, I've talked about the fact that we were from an actual standpoint in 2025, 15.2% adjusted IFO. As you move to 2026, you've got the guided range of 15%-16%. Underneath or within that market, there's the much higher growth opportunities associated with AI native, AI foundational, and then we've talked off and on throughout the day about kind of the more greenfield opportunities for EPAM, agentic BPO, AI-enabled managed services. underneath or within that market there's the much higher growth opportunities associated with ai native ai foundational and then we've talked off and on throughout the day about kind of the more greenfield opportunities for epam agentic bpo ai-enabled managed services There'll probably be some contribution from M&A over time. there'll probably be some contribution from m&a over time What we are looking to do is continue to accelerate our revenue growth by participating and, more importantly, succeeding in the high-growth markets. what we are looking to do is continue to accelerate our revenue growth by participating and more importantly succeeding in the high-growth markets With a goal of eventually returning to 10% or a double-digit organic constant currency revenue growth. with a goal of eventually returning to 10% or a double-digit organic constant currency revenue growth From a profitability standpoint, you know, I've talked about the fact that we were from an actual standpoint in 2025, 15.2% adjusted IFO. from a profitability standpoint you know i've talked about the fact that we were from an actual standpoint in 2025 15.2% adjusted ifo As you move to 2026, you've got the guided range of 15%-16%. as you move to 2026 you've got the guided range of 15%-16% What we're looking to do is continue to improve profitability over the next couple of years. Returning to a 16%+ in 2028. Again, what we'd be focused on is both improving gross margins and then in 2027 and 2028, also gaining some additional benefit from SG&A. I think I've talked over the last couple of quarters about our focus right now is to continue to invest in business development and sort of sales-focused marketing. I don't expect us to see a lot of leverage in SG&A in 2026. Instead, what you'll see, gross margin expansion. Then over time, you'll see a little bit more efficiency benefit from SG&A. At the same time, you know, we're focused on generating between 50 and 70 basis points gross margin improvement. What we're looking to do is continue to improve profitability over the next couple of years. what we're looking to do is continue to improve profitability over the next couple of years Returning to a 16%+ in 2028. returning to a 16%+ in 2028 Again, what we'd be focused on is both improving gross margins and then in 2027 and 2028, also gaining some additional benefit from SG&A. again what we'd be focused on is both improving gross margins and then in 2027 and 2028 also gaining some additional benefit from sg&a I think I've talked over the last couple of quarters about our focus right now is to continue to invest in business development and sort of sales-focused marketing. i think i've talked over the last couple of quarters about our focus right now is to continue to invest in business development and sort of sales-focused marketing I don't expect us to see a lot of leverage in SG&A in 2026. i don't expect us to see a lot of leverage in sg&a in 2026 Instead, what you'll see, gross margin expansion. instead what you'll see gross margin expansion Then over time, you'll see a little bit more efficiency benefit from SG&A. then over time you'll see a little bit more efficiency benefit from sg&a At the same time, you know, we're focused on generating between 50 and 70 basis points gross margin improvement. at the same time you know we're focused on generating between 50 and 70 basis points gross margin improvement After 2026, that would come from the cost efficiencies, that would come from the pyramid or seniority index we've talked about. Nothing heroic, just kinda returning back in the direction of what we might have generated historically. Utilization improvement and then the AI associated benefits, again, sharing those with our clients. From a free cash flow generation standpoint, we've always had strong free cash flows or generated strong free cash flows, over $500 million in 2023, over $500 million in 2024. More recently, we actually generated over $600 million in 2026. As I look forward, you know, we'd be committed to continuing to maintain the 80%-90% conversion rate that we have historically targeted. After 2026, that would come from the cost efficiencies, that would come from the pyramid or seniority index we've talked about. after 2026 that would come from the cost efficiencies that would come from the pyramid or seniority index we've talked about Nothing heroic, just kinda returning back in the direction of what we might have generated historically. nothing heroic just kinda returning back in the direction of what we might have generated historically Utilization improvement and then the AI associated benefits, again, sharing those with our clients. utilization improvement and then the ai associated benefits again sharing those with our clients From a free cash flow generation standpoint, we've always had strong free cash flows or generated strong free cash flows, over $500 million in 2023, over $500 million in 2024. from a free cash flow generation standpoint we've always had strong free cash flows or generated strong free cash flows over $500 million in 2023 over $500 million in 2024 More recently, we actually generated over $600 million in 2026. more recently we actually generated over $600 million in 2026 As I look forward, you know, we'd be committed to continuing to maintain the 80%-90% conversion rate that we have historically targeted. as i look forward you know we'd be committed to continuing to maintain the 80%-90% conversion rate that we have historically targeted As I look at our financials over time, that means we would generate over $1.8 billion plus in free cash flows over the time period 2026 through 2028. I think most of us are aware of the fact that the company's got a very strong balance sheet. At the end of 2025, we had $1.3 billion in cash. We have modest debt. We have a untapped credit facility. On top of that, we've got the ability to generate the $1.8 billion in free cash flows that I talked about. As we look over the last couple of years, our historic use of cash clearly we invest in our business. As I look at our financials over time, that means we would generate over $1.8 billion plus in free cash flows over the time period 2026 through 2028. as i look at our financials over time that means we would generate over $1.8 billion plus in free cash flows over the time period 2026 through 2028 I think most of us are aware of the fact that the company's got a very strong balance sheet. i think most of us are aware of the fact that the company's got a very strong balance sheet At the end of 2025, we had $1.3 billion in cash. at the end of 2025 we had $1.3 billion in cash We have modest debt. we have modest debt We have a untapped credit facility. we have a untapped credit facility On top of that, we've got the ability to generate the $1.8 billion in free cash flows that I talked about. on top of that we've got the ability to generate the $1.8 billion in free cash flows that i talked about As we look over the last couple of years, our historic use of cash clearly we invest in our business. as we look over the last couple of years our historic use of cash clearly we invest in our business I think we've talked about this throughout today, right, in terms of the skill development, the education, the platform technologies, the AI capabilities, the IP and the assets. We're spending hundreds of millions of dollars on that. That keeps us at the cutting edge and gives us the opportunity to continue to grow faster than the rest of the market. We'll continue to make those investments. We'll continue to do strategic acquisitions. Then over the last couple of years, we also introduced share repurchases. We would continue to do those. Off to the right here, we'll continue to reinvest in the business. You'll have capital returns in the form of share repurchases and of the $1 billion that was authorized. Most recently, we still have $450 million left in that. I think we've talked about this throughout today, right, in terms of the skill development, the education, the platform technologies, the AI capabilities, the IP and the assets. i think we've talked about this throughout today right in terms of the skill development the education the platform technologies the ai capabilities the ip and the assets We're spending hundreds of millions of dollars on that. we're spending hundreds of millions of dollars on that That keeps us at the cutting edge and gives us the opportunity to continue to grow faster than the rest of the market. that keeps us at the cutting edge and gives us the opportunity to continue to grow faster than the rest of the market We'll continue to make those investments. we'll continue to make those investments We'll continue to do strategic acquisitions. we'll continue to do strategic acquisitions Then over the last couple of years, we also introduced share repurchases. then over the last couple of years we also introduced share repurchases We would continue to do those. we would continue to do those Off to the right here, we'll continue to reinvest in the business. off to the right here we'll continue to reinvest in the business You'll have capital returns in the form of share repurchases and of the $1 billion that was authorized. you'll have capital returns in the form of share repurchases and of the $1 billion that was authorized Most recently, we still have $450 million left in that. most recently we still have $450 million left in that Finally, you'd continue to see some level of M&A, probably more in the tuck-in category in 2026. If I then just sort of close here on the M&A objectives, you know, we clearly would look to sort of expand our in-market capabilities, particularly, industry vertical capabilities, and clearly that augments our AI capabilities. We also might use M&A to help us, you know, effectively be an entry point for select geographies. This is the type of idea where you sort of create a beachhead, which then you can grow behind. Finally, we would use M&A to sort of deepen the scale of certain high-growth capabilities. Finally, you'd continue to see some level of M&A, probably more in the tuck-in category in 2026. finally you'd continue to see some level of m&a probably more in the tuck-in category in 2026 If I then just sort of close here on the M&A objectives, you know, we clearly would look to sort of expand our in-market capabilities, particularly, industry vertical capabilities, and clearly that augments our AI capabilities. if i then just sort of close here on the m&a objectives you know we clearly would look to sort of expand our in-market capabilities particularly industry vertical capabilities and clearly that augments our ai capabilities We also might use M&A to help us, you know, effectively be an entry point for select geographies. we also might use m&a to help us you know effectively be an entry point for select geographies This is the type of idea where you sort of create a beachhead, which then you can grow behind. this is the type of idea where you sort of create a beachhead which then you can grow behind Finally, we would use M&A to sort of deepen the scale of certain high-growth capabilities. finally we would use m&a to sort of deepen the scale of certain high-growth capabilities I've always thought of our M&A strategy as one that is not necessarily designed to buy revenue, but it's really designed to sort of help shift the company, to create an opportunity for the company to address different opportunities and then further our organic constant currency growth rate. Most of the companies we acquire do have our services businesses, so there's strong free cash flows. Finally, our historic focus has been to make certain that we're able to sort of maintain the 16%+ profitability. Over the last couple of years, we got away from that. In the future, what you'd see is we'd make certain that we did acquisitions that allowed us to either achieve the 16% or actually sort of facilitated the achievement of the 16% profitability range. I've always thought of our M&A strategy as one that is not necessarily designed to buy revenue, but it's really designed to sort of help shift the company, to create an opportunity for the company to address different opportunities and then further our organic constant currency growth rate. i've always thought of our m&a strategy as one that is not necessarily designed to buy revenue but it's really designed to sort of help shift the company to create an opportunity for the company to address different opportunities and then further our organic constant currency growth rate Most of the companies we acquire do have our services businesses, so there's strong free cash flows. most of the companies we acquire do have our services businesses so there's strong free cash flows Finally, our historic focus has been to make certain that we're able to sort of maintain the 16%+ profitability. finally our historic focus has been to make certain that we're able to sort of maintain the 16%+ profitability Over the last couple of years, we got away from that. over the last couple of years we got away from that In the future, what you'd see is we'd make certain that we did acquisitions that allowed us to either achieve the 16% or actually sort of facilitated the achievement of the 16% profitability range. in the future what you'd see is we'd make certain that we did acquisitions that allowed us to either achieve the 16% or actually sort of facilitated the achievement of the 16% profitability range In conclusion, we're focused on ongoing acceleration in revenue growth. We intend to continue to improve profitability, returning to the 16%+ adjusted IFO level by 2028. We're gonna continue to generate strong free cash flows, the $1.8 billion+ that I've been talking about. We'll continue to make disciplined capital allocations, including share repurchases. Again, with that's the end of my presentation. We are gonna have Q&A after this, but right now we've got one more customer video. I think it's Bank of Ireland, and thank you very much. In conclusion, we're focused on ongoing acceleration in revenue growth. in conclusion we're focused on ongoing acceleration in revenue growth We intend to continue to improve profitability, returning to the 16%+ adjusted IFO level by 2028. we intend to continue to improve profitability returning to the 16%+ adjusted ifo level by 2028 We're gonna continue to generate strong free cash flows, the $1.8 billion+ that I've been talking about. we're gonna continue to generate strong free cash flows the $1.8 billion+ that i've been talking about We'll continue to make disciplined capital allocations, including share repurchases. we'll continue to make disciplined capital allocations including share repurchases Again, with that's the end of my presentation. again with that's the end of my presentation We are gonna have Q&A after this, but right now we've got one more customer video. we are gonna have q&a after this but right now we've got one more customer video I think it's Bank of Ireland, and thank you very much. i think it's bank of ireland and thank you very much

Speaker 25: Hi, I'm Myles O'Grady, Chief Executive of Bank of Ireland Group. I want to share the story about our new app, which EPAM has strongly supported us on, launching in the coming months. As we all know, customer expectations have changed fast and continue to evolve at pace. Keeping up isn't enough. We need to ensure our technology is market-leading. We've implemented change and made improvements with increasing momentum. We've upgraded systems across the bank, delivering greater stability and resilience and better customer service. We've invested in technology that our customers use most, facilitating payments across Europe in seconds and upgrading our digital banking offering. AI has helped us protect customers more and do things faster and better. A core focus has also been the reinvention of our mobile banking app, a hugely important part of customer service offering. Hi, I'm Myles O'Grady, Chief Executive of Bank of Ireland Group. hi i'm myles o'grady chief executive of bank of ireland group I want to share the story about our new app, which EPAM has strongly supported us on, launching in the coming months. i want to share the story about our new app which epam has strongly supported us on launching in the coming months As we all know, customer expectations have changed fast and continue to evolve at pace. as we all know customer expectations have changed fast and continue to evolve at pace Keeping up isn't enough. keeping up isn't enough We need to ensure our technology is market-leading. we need to ensure our technology is market-leading We've implemented change and made improvements with increasing momentum. we've implemented change and made improvements with increasing momentum We've upgraded systems across the bank, delivering greater stability and resilience and better customer service. we've upgraded systems across the bank delivering greater stability and resilience and better customer service We've invested in technology that our customers use most, facilitating payments across Europe in seconds and upgrading our digital banking offering. we've invested in technology that our customers use most facilitating payments across europe in seconds and upgrading our digital banking offering AI has helped us protect customers more and do things faster and better. A core focus has also been the reinvention of our mobile banking app, a hugely important part of customer service offering. ai has helped us protect customers more and do things faster and better. a core focus has also been the reinvention of our mobile banking app a hugely important part of customer service offering We have been working closely with EPAM on this, and I know they understand our vision and ambition for what we want to deliver here. The result is a banking app in pilot right now and launching soon that we can be proud of, that will deliver great outcomes every day for our customers, and will help us go further, faster over the time ahead. 2025 was a transformational year for Bank of Ireland in our tech delivery, and this year promises to be even more exciting. I'd like to thank FB, Arc, and all the team at EPAM for their strong support in the progress we are making and in the delivery of our ambitious plans for the future. We're looking forward to the journey ahead and to what we can achieve together. We have been working closely with EPAM on this, and I know they understand our vision and ambition for what we want to deliver here. we have been working closely with epam on this and i know they understand our vision and ambition for what we want to deliver here The result is a banking app in pilot right now and launching soon that we can be proud of, that will deliver great outcomes every day for our customers, and will help us go further, faster over the time ahead. 2025 was a transformational year for Bank of Ireland in our tech delivery, and this year promises to be even more exciting. the result is a banking app in pilot right now and launching soon that we can be proud of that will deliver great outcomes every day for our customers and will help us go further faster over the time ahead 2025 was a transformational year for bank of ireland in our tech delivery and this year promises to be even more exciting I'd like to thank FB, Arc, and all the team at EPAM for their strong support in the progress we are making and in the delivery of our ambitious plans for the future. i'd like to thank fb arc and all the team at epam for their strong support in the progress we are making and in the delivery of our ambitious plans for the future We're looking forward to the journey ahead and to what we can achieve together. we're looking forward to the journey ahead and to what we can achieve together

Speaker 24: Okay. A lot of content today. We've got our final Q&A session with several of our leaders. Same rules as the first session, so please raise your hand if you have a question. Allow the mic to come to you. Raise your hand. Excuse me. State your name and firm. For those online, if you submit a question, we are looking, we'll field those as well. Let's go with the first question right here. The glasses. Okay. A lot of content today. okay. a lot of content today We've got our final Q&A session with several of our leaders. we've got our final q&a session with several of our leaders Same rules as the first session, so please raise your hand if you have a question. same rules as the first session so please raise your hand if you have a question Allow the mic to come to you. allow the mic to come to you Raise your hand. raise your hand Excuse me. excuse me State your name and firm. state your name and firm For those online, if you submit a question, we are looking, we'll field those as well. for those online if you submit a question we are looking we'll field those as well Let's go with the first question right here. let's go with the first question right here The glasses. the glasses

Speaker 9: Thank you. Thank you. thank you

Speaker 24: Yeah. Yeah. yeah

Speaker 9: Thanks. It's David Grossman from Stifel. You know, you did a great job of laying out the structural tailwinds from AI and why EPAM is well-positioned, you know, to benefit from those tailwinds. I think what's notable is, you know, historically at least, these massive changes in technology have been accompanied by accelerating growth for the industry. On the other hand, industry growth has been relatively low, you know, call it the last 18-24 months. In your opinion, what is so different structurally about this cycle, and what needs to happen for growth to not only re-accelerate for the industry, but obviously for EPAM as well? Thanks. thanks It's David Grossman from Stifel. it's david grossman from stifel You know, you did a great job of laying out the structural tailwinds from AI and why EPAM is well-positioned, you know, to benefit from those tailwinds. you know you did a great job of laying out the structural tailwinds from ai and why epam is well-positioned you know to benefit from those tailwinds I think what's notable is, you know, historically at least, these massive changes in technology have been accompanied by accelerating growth for the industry. i think what's notable is you know historically at least these massive changes in technology have been accompanied by accelerating growth for the industry On the other hand, industry growth has been relatively low, you know, call it the last 18-24 months. on the other hand industry growth has been relatively low you know call it the last 18-24 months In your opinion, what is so different structurally about this cycle, and what needs to happen for growth to not only re-accelerate for the industry, but obviously for EPAM as well? in your opinion what is so different structurally about this cycle and what needs to happen for growth to not only re-accelerate for the industry but obviously for epam as well

Speaker 6: David, good to see you, let me try to address that. I think what's really different at this time is the rate of change of these fundamental technologies are so much faster. Our clients, ourselves, and everybody who is participating in this is just watching the race, what we are seeing. It's what somebody in the audience we discussed it already this morning, that some people are just waiting till things gets cheaper, right? They are waiting for if you wait one more month, maybe the model will get better. Maybe if you wait one more month, maybe the model not just gets better, it gets cheaper. Just probably six months ago, when we reached the point where the model's results are good enough and they're cheap enough that you actually can launch these transformational programs. David, good to see you, let me try to address that. david good to see you let me try to address that I think what's really different at this time is the rate of change of these fundamental technologies are so much faster. i think what's really different at this time is the rate of change of these fundamental technologies are so much faster Our clients, ourselves, and everybody who is participating in this is just watching the race, what we are seeing. our clients ourselves and everybody who is participating in this is just watching the race what we are seeing It's what somebody in the audience we discussed it already this morning, that some people are just waiting till things gets cheaper, right? it's what somebody in the audience we discussed it already this morning that some people are just waiting till things gets cheaper right They are waiting for if you wait one more month, maybe the model will get better. they are waiting for if you wait one more month maybe the model will get better Maybe if you wait one more month, maybe the model not just gets better, it gets cheaper. maybe if you wait one more month maybe the model not just gets better it gets cheaper Just probably six months ago, when we reached the point where the model's results are good enough and they're cheap enough that you actually can launch these transformational programs. just probably six months ago when we reached the point where the model's results are good enough and they're cheap enough that you actually can launch these transformational programs I think we got so accustomed to that people rush ahead and allocate capital and start making these investments that we underestimate the resistance and the time and cautiousness people are having with these new AI models, because it's no longer just an IT change. Cloud was the internal affairs of the IT department. This is a business change. This requires business leader committing to a massive change program, how to change the whole business processes, and also addressing the technical debt which they're carrying today. Because without addressing the foundational element of AI, which we keep talking about it, the cloud migration, the data and data product creation, the legacy modernization, you're not going to get the benefits. You need to upskill your teams. I think we got so accustomed to that people rush ahead and allocate capital and start making these investments that we underestimate the resistance and the time and cautiousness people are having with these new AI models, because it's no longer just an IT change. i think we got so accustomed to that people rush ahead and allocate capital and start making these investments that we underestimate the resistance and the time and cautiousness people are having with these new ai models because it's no longer just an it change Cloud was the internal affairs of the IT department. cloud was the internal affairs of the it department This is a business change. this is a business change This requires business leader committing to a massive change program, how to change the whole business processes, and also addressing the technical debt which they're carrying today. this requires business leader committing to a massive change program how to change the whole business processes and also addressing the technical debt which they're carrying today Because without addressing the foundational element of AI, which we keep talking about it, the cloud migration, the data and data product creation, the legacy modernization, you're not going to get the benefits. because without addressing the foundational element of ai which we keep talking about it the cloud migration the data and data product creation the legacy modernization you're not going to get the benefits You need to upskill your teams. you need to upskill your teams Everybody's reluctant to get locked in to a vendor, locked into an engagement model, and everybody's hoping that they can do this without massive changes to their organization. This has created kind of, I would say, a wait-and-see period. Now what we are feeling that organizations are no longer able to wait longer. They are just ready to launch into it, and we have these active discussions, which makes us very optimistic that going forward we're going to see the demand bouncing back. Now, when do we see it for the whole industry to start doing that? When one player, one client of ours or maybe a client of our competitors actually succeed with the transformation. One Everybody's reluctant to get locked in to a vendor, locked into an engagement model, and everybody's hoping that they can do this without massive changes to their organization. everybody's reluctant to get locked in to a vendor locked into an engagement model and everybody's hoping that they can do this without massive changes to their organization This has created kind of, I would say, a wait-and-see period. this has created kind of i would say a wait-and-see period Now what we are feeling that organizations are no longer able to wait longer. now what we are feeling that organizations are no longer able to wait longer They are just ready to launch into it, and we have these active discussions, which makes us very optimistic that going forward we're going to see the demand bouncing back. they are just ready to launch into it and we have these active discussions which makes us very optimistic that going forward we're going to see the demand bouncing back Now, when do we see it for the whole industry to start doing that? now when do we see it for the whole industry to start doing that When one player, one client of ours or maybe a client of our competitors actually succeed with the transformation. when one player one client of ours or maybe a client of our competitors actually succeed with the transformation One one Maybe they don't even have to do the full-blown transformation of a whole company, but if you transform just one line of a business and achieve some level of efficiency gains or speed to the market, which we never seen before, that will force everybody else in that vertical, in that geography to do the same and do transformation en masse. I think this is where we are, and we are in this tipping point. This is the first time when you start hearing from the frontier players, the Anthropic, the OpenAI, that they actually done the engineering and they actually now seeing that the first time he really saw real efficiency gains from software engineering using AI, something which really surprising. Maybe they don't even have to do the full-blown transformation of a whole company, but if you transform just one line of a business and achieve some level of efficiency gains or speed to the market, which we never seen before, that will force everybody else in that vertical, in that geography to do the same and do transformation en masse. maybe they don't even have to do the full-blown transformation of a whole company but if you transform just one line of a business and achieve some level of efficiency gains or speed to the market which we never seen before that will force everybody else in that vertical in that geography to do the same and do transformation en masse I think this is where we are, and we are in this tipping point. i think this is where we are and we are in this tipping point This is the first time when you start hearing from the frontier players, the Anthropic, the OpenAI, that they actually done the engineering and they actually now seeing that the first time he really saw real efficiency gains from software engineering using AI, something which really surprising. this is the first time when you start hearing from the frontier players the anthropic the openai that they actually done the engineering and they actually now seeing that the first time he really saw real efficiency gains from software engineering using ai something which really surprising The first time he actually trusted the AI to do the coding was late last year. I think we just underestimated how much time it will take to get to this stage, and we are there. Now it's going to start happening. The first time he actually trusted the AI to do the coding was late last year. I think we just underestimated how much time it will take to get to this stage, and we are there. the first time he actually trusted the ai to do the coding was late last year. i think we just underestimated how much time it will take to get to this stage and we are there Now it's going to start happening. now it's going to start happening

Speaker 24: Maybe in the back. Great. Maybe in the back. maybe in the back Great. great

Speaker 22: Hi. Oh, yeah. Thank you so much. Hi, Maggie Nolan with William Blair. Why is vertical expertise more important now? EPAM has a broad set of verticals that they address. Do you need to narrow that focus, or are there ones that you're going to start with first to maximize success? Hi. hi Oh, yeah. oh yeah Thank you so much. thank you so much Hi, Maggie Nolan with William Blair. hi maggie nolan with william blair Why is vertical expertise more important now? why is vertical expertise more important now EPAM has a broad set of verticals that they address. epam has a broad set of verticals that they address Do you need to narrow that focus, or are there ones that you're going to start with first to maximize success? do you need to narrow that focus or are there ones that you're going to start with first to maximize success

Speaker 6: Maggie, good to see you, and I think it's a good question. Why now? In the digital transformation space, horizontal skill sets were much more important. People were actually applying horizontal capabilities into variety of industries. During the AI transformation, on the other hand, they have to solve business problems. They have to now tackle the business challenges. That requires real industry knowledge. That requires you to discover how to automate that piece of functionality. That requires you to really understand deeply what to do. You can walk around and you will see how we are tackling it in energy, how we're doing it in healthcare, life sciences. In order to do that, you really need to understand what you're doing because as Vic mentioned, the models will hallucinate. Maggie, good to see you, and I think it's a good question. maggie good to see you and i think it's a good question Why now? why now In the digital transformation space, horizontal skill sets were much more important. in the digital transformation space horizontal skill sets were much more important People were actually applying horizontal capabilities into variety of industries. people were actually applying horizontal capabilities into variety of industries During the AI transformation, on the other hand, they have to solve business problems. during the ai transformation on the other hand they have to solve business problems They have to now tackle the business challenges. they have to now tackle the business challenges That requires real industry knowledge. that requires real industry knowledge That requires you to discover how to automate that piece of functionality. that requires you to discover how to automate that piece of functionality That requires you to really understand deeply what to do. that requires you to really understand deeply what to do You can walk around and you will see how we are tackling it in energy, how we're doing it in healthcare, life sciences. you can walk around and you will see how we are tackling it in energy how we're doing it in healthcare life sciences In order to do that, you really need to understand what you're doing because as Vic mentioned, the models will hallucinate. in order to do that you really need to understand what you're doing because as vic mentioned the models will hallucinate If you're not grounding it into vertical expertise, what you're going to produce is not going to be safe. If you look at LivaNova case study, which is an AI engineering case study, the fact that they've got their software FDA approved, and by the way, we used a ton of agentic solutions, it underlines what you need to bring to the table in order to make it safe, in order to make it really productive in this environment. Vic, Elaina, do you want to add something to it? If you're not grounding it into vertical expertise, what you're going to produce is not going to be safe. if you're not grounding it into vertical expertise what you're going to produce is not going to be safe If you look at LivaNova case study, which is an AI engineering case study, the fact that they've got their software FDA approved, and by the way, we used a ton of agentic solutions, it underlines what you need to bring to the table in order to make it safe, in order to make it really productive in this environment. if you look at livanova case study which is an ai engineering case study the fact that they've got their software fda approved and by the way we used a ton of agentic solutions it underlines what you need to bring to the table in order to make it safe in order to make it really productive in this environment Vic, Elaina, do you want to add something to it? vic elaina do you want to add something to it

Speaker 11: I think the cycle change that we see is broadly a move from digitizing businesses, which is what we've been doing for the past 10 years, you know, with cloud and modernization, to transforming them. I know we've been using digital transformation kind of as an industry term. I think we're really on the forefront of actual business transformation. It's not just digitizing or creating data platforms. It's actually reimagining new business models with an AI-centric point of view. That's hard technically hard, but it's even more difficult from an industry point of view because particularly in regulated industries, you don't just get to try it and see if it sticks. I think the cycle change that we see is broadly a move from digitizing businesses, which is what we've been doing for the past 10 years, you know, with cloud and modernization, to transforming them. i think the cycle change that we see is broadly a move from digitizing businesses which is what we've been doing for the past 10 years you know with cloud and modernization to transforming them I know we've been using digital transformation kind of as an industry term. i know we've been using digital transformation kind of as an industry term I think we're really on the forefront of actual business transformation. i think we're really on the forefront of actual business transformation It's not just digitizing or creating data platforms. it's not just digitizing or creating data platforms It's actually reimagining new business models with an AI-centric point of view. it's actually reimagining new business models with an ai-centric point of view That's hard technically hard, but it's even more difficult from an industry point of view because particularly in regulated industries, you don't just get to try it and see if it sticks. that's hard technically hard but it's even more difficult from an industry point of view because particularly in regulated industries you don't just get to try it and see if it sticks

Speaker 34: Maybe one more thing. We have actually we are not starting from scratch. Like, from 2014 or 2015, we are building healthcare and life science at scale of the whole organization end to end. You will see Greg today, he will see it and show it, and it's engineering, it's consulting, it's advisory strategy in all the levels. It's a good question about focusing, but we are doing it, and so it's improvement. It's not necessarily you need to be locked in somewhere. The same happening with energy from 2016, from large workloads there, and so time after time, gaming. You see it with us actually over time. Maybe one more thing. maybe one more thing We have actually we are not starting from scratch. we have actually we are not starting from scratch Like, from 2014 or 2015, we are building healthcare and life science at scale of the whole organization end to end. like from 2014 or 2015 we are building healthcare and life science at scale of the whole organization end to end You will see Greg today, he will see it and show it, and it's engineering, it's consulting, it's advisory strategy in all the levels. you will see greg today he will see it and show it and it's engineering it's consulting it's advisory strategy in all the levels It's a good question about focusing, but we are doing it, and so it's improvement. it's a good question about focusing but we are doing it and so it's improvement It's not necessarily you need to be locked in somewhere. it's not necessarily you need to be locked in somewhere The same happening with energy from 2016, from large workloads there, and so time after time, gaming. the same happening with energy from 2016 from large workloads there and so time after time gaming You see it with us actually over time. you see it with us actually over time

Speaker 24: Let's go here. Let's go here. let's go here

Speaker 33: Surinder Thind with Jefferies. As you think about the build part of the equation and you start to build bigger and more complex platforms and all of the orchestration that's going to be on top of that in terms of the agents, who at the end of the day owns the IP, and do you have the ability to maybe manage or run those platforms and monetize the agents or the capabilities, or does EPAM still remain within the build part, and then you just kind of let your clients run the platforms at that point? I don't want to say you walk away, but then you work on the next project. Surinder Thind with Jefferies. surinder thind with jefferies As you think about the build part of the equation and you start to build bigger and more complex platforms and all of the orchestration that's going to be on top of that in terms of the agents, who at the end of the day owns the IP, and do you have the ability to maybe manage or run those platforms and monetize the agents or the capabilities, or does EPAM still remain within the build part, and then you just kind of let your clients run the platforms at that point? as you think about the build part of the equation and you start to build bigger and more complex platforms and all of the orchestration that's going to be on top of that in terms of the agents who at the end of the day owns the ip and do you have the ability to maybe manage or run those platforms and monetize the agents or the capabilities or does epam still remain within the build part and then you just kind of let your clients run the platforms at that point I don't want to say you walk away, but then you work on the next project. i don't want to say you walk away but then you work on the next project

Speaker 6: Thank you very much. I think it's hard to see where this leads to. I think we're already in the position that the build versus buy equation is flipping. We are starting to build more, and the clients are choosing to build more instead of buying off-the-shelf packages or SaaS solutions. We are actually rebuilding some of these SaaS solutions for the clients to take it in-house. In the current wave, what we're seeing is that people want to own their own IP, especially when you are talking about agents. Remember, this is a workforce transformation. You want to own your own workforce. Even if your workforce is no longer humans, they could be agents. You as an organization, you have to risk mitigate. You are dependent on your workforce. Thank you very much. thank you very much I think it's hard to see where this leads to. i think it's hard to see where this leads to I think we're already in the position that the build versus buy equation is flipping. i think we're already in the position that the build versus buy equation is flipping We are starting to build more, and the clients are choosing to build more instead of buying off-the-shelf packages or SaaS solutions. we are starting to build more and the clients are choosing to build more instead of buying off-the-shelf packages or saas solutions We are actually rebuilding some of these SaaS solutions for the clients to take it in-house. we are actually rebuilding some of these saas solutions for the clients to take it in-house In the current wave, what we're seeing is that people want to own their own IP, especially when you are talking about agents. in the current wave what we're seeing is that people want to own their own ip especially when you are talking about agents Remember, this is a workforce transformation. remember this is a workforce transformation You want to own your own workforce. you want to own your own workforce Even if your workforce is no longer humans, they could be agents. even if your workforce is no longer humans they could be agents You as an organization, you have to risk mitigate. you as an organization you have to risk mitigate You are dependent on your workforce. you are dependent on your workforce We are seeing clients really want to own the agents themselves. They want to have flexibility. This is at the next level of risk management. You cannot be locked into a vendor like EPAM or even to a model or even to hyperscalers because now your whole business starts dependent on that workforce. I think we have to start seeing this transformation itself in a very different eye. We have to see it as a workforce or actually whole business transformation and less on IT transformation. Once you start seeing it from that angle, I had these discussions just the other week with an insurer. They are seeing this from a risk management point of view. Who owns the agent itself? We are seeing clients really want to own the agents themselves. we are seeing clients really want to own the agents themselves They want to have flexibility. they want to have flexibility This is at the next level of risk management. this is at the next level of risk management You cannot be locked into a vendor like EPAM or even to a model or even to hyperscalers because now your whole business starts dependent on that workforce. you cannot be locked into a vendor like epam or even to a model or even to hyperscalers because now your whole business starts dependent on that workforce I think we have to start seeing this transformation itself in a very different eye. i think we have to start seeing this transformation itself in a very different eye We have to see it as a workforce or actually whole business transformation and less on IT transformation. we have to see it as a workforce or actually whole business transformation and less on it transformation Once you start seeing it from that angle, I had these discussions just the other week with an insurer. once you start seeing it from that angle i had these discussions just the other week with an insurer They are seeing this from a risk management point of view. they are seeing this from a risk management point of view Who owns the agent itself? who owns the agent itself In the end of the transformation, they're letting go their original workforce, and now they are relying on a new agentic workforce. I mean, that equation, your business dependency is switching, and they wanna own that dependency. In the end of the transformation, they're letting go their original workforce, and now they are relying on a new agentic workforce. I mean, that equation, your business dependency is switching, and they wanna own that dependency. in the end of the transformation they're letting go their original workforce and now they are relying on a new agentic workforce. i mean that equation your business dependency is switching and they wanna own that dependency

Speaker 11: Can I just? Can I just? can i just

Speaker 6: Yes. Yes. yes

Speaker 11: There's not just the IP over the build versus buy. The critical sort of rights issue is to the data, and it actually is probably one of the reasons why, you know, the frontier companies will likely not end up owning the full end-to-end because there is a critical mission type of not just rules and logic, but actually the ownership over their own data. Yes, we can maybe operate some of the platforms that we design and build, but it would be a rare thing where we would be the owners and controllers of the underlying enterprise data set. There's not just the IP over the build versus buy. there's not just the ip over the build versus buy The critical sort of rights issue is to the data, and it actually is probably one of the reasons why, you know, the frontier companies will likely not end up owning the full end-to-end because there is a critical mission type of not just rules and logic, but actually the ownership over their own data. the critical sort of rights issue is to the data and it actually is probably one of the reasons why you know the frontier companies will likely not end up owning the full end-to-end because there is a critical mission type of not just rules and logic but actually the ownership over their own data Yes, we can maybe operate some of the platforms that we design and build, but it would be a rare thing where we would be the owners and controllers of the underlying enterprise data set. yes we can maybe operate some of the platforms that we design and build but it would be a rare thing where we would be the owners and controllers of the underlying enterprise data set

Speaker 24: Let's go here. Let's go here. let's go here

Speaker 28: Hi. Phani Kanumuri from HSBC. As you said, the technology is evolving very rapidly, so how do you ensure that your employees are upskill in such a fast-changing technology? And how do you price in this technology? As AI native services likely requires a long contract period, so how do you price in these kind of changes? Hi. hi Phani Kanumuri from HSBC. phani kanumuri from hsbc As you said, the technology is evolving very rapidly, so how do you ensure that your employees are upskill in such a fast-changing technology? as you said the technology is evolving very rapidly so how do you ensure that your employees are upskill in such a fast-changing technology And how do you price in this technology? and how do you price in this technology As AI native services likely requires a long contract period, so how do you price in these kind of changes? as ai native services likely requires a long contract period so how do you price in these kind of changes

Speaker 6: That's a very interesting question. I think we already saw in this AI transformation space probably two or three technology shifts by this point, right? I do remember when Andrei Zahorodniuk very proudly launched the next generation AI architecture, which is probably six or eight months later was out of date. I don't know if you remember the RAG architectures and all the different vector databases, which everybody was crazy about probably 18 months ago, 12 months ago. Today, nobody talks about it anymore because the context window grows so much. I think staying on the frontier is requires you to continuously do R&D, continuously have people who are on the frontier and actually on the edge of the model. That's a very interesting question. that's a very interesting question I think we already saw in this AI transformation space probably two or three technology shifts by this point, right? i think we already saw in this ai transformation space probably two or three technology shifts by this point right I do remember when Andrei Zahorodniuk very proudly launched the next generation AI architecture, which is probably six or eight months later was out of date. i do remember when andrei zahorodniuk very proudly launched the next generation ai architecture which is probably six or eight months later was out of date I don't know if you remember the RAG architectures and all the different vector databases, which everybody was crazy about probably 18 months ago, 12 months ago. i don't know if you remember the rag architectures and all the different vector databases which everybody was crazy about probably 18 months ago 12 months ago Today, nobody talks about it anymore because the context window grows so much. today nobody talks about it anymore because the context window grows so much I think staying on the frontier is requires you to continuously do R&D, continuously have people who are on the frontier and actually on the edge of the model. i think staying on the frontier is requires you to continuously do r&d continuously have people who are on the frontier and actually on the edge of the model We have team members working evaluating, building new types of capabilities, in-house, and from that, designing new types of educational programs. The educational programs which Sandra and Alexei was talking about, how we pushing it out. I think Vic was also indicating that we codified the environment which we are operating. In reality, we are running the internal systems with agents, with MCP connections to the internal application, so you can actually run operations as a code in the organization. This is a very different shift. But how you educating them continuously, how you are actually making them work continuously, we're running program. Maybe Larry or Vic wanna talk about this. We have team members working evaluating, building new types of capabilities, in-house, and from that, designing new types of educational programs. we have team members working evaluating building new types of capabilities in-house and from that designing new types of educational programs The educational programs which Sandra and Alexei was talking about, how we pushing it out. the educational programs which sandra and alexei was talking about how we pushing it out I think Vic was also indicating that we codified the environment which we are operating. i think vic was also indicating that we codified the environment which we are operating In reality, we are running the internal systems with agents, with MCP connections to the internal application, so you can actually run operations as a code in the organization. in reality we are running the internal systems with agents with mcp connections to the internal application so you can actually run operations as a code in the organization This is a very different shift. this is a very different shift But how you educating them continuously, how you are actually making them work continuously, we're running program. but how you educating them continuously how you are actually making them work continuously we're running program Maybe Larry or Vic wanna talk about this. maybe larry or vic wanna talk about this

Speaker 20: Yeah. Just the one thing I was gonna add is, to some degree, a lot of this starts from the beginning, from the selection, and we have very, very rigorous technical requirements and expertise that comes from EPAM that starts even before the individual joins the company. We try to only include in that pipeline of candidates that we select those that we believe have the strongest technical chops. Yeah. yeah Just the one thing I was gonna add is, to some degree, a lot of this starts from the beginning, from the selection, and we have very, very rigorous technical requirements and expertise that comes from EPAM that starts even before the individual joins the company. just the one thing i was gonna add is to some degree a lot of this starts from the beginning from the selection and we have very very rigorous technical requirements and expertise that comes from epam that starts even before the individual joins the company We try to only include in that pipeline of candidates that we select those that we believe have the strongest technical chops. we try to only include in that pipeline of candidates that we select those that we believe have the strongest technical chops

Speaker 34: Just to continue on this. This is very important comment because one of the key differentiators of the AI agentic engineers is judgment. We actually continuously, and this is what Arkadiy Dobkin started to say, we were selecting people with judgment all the time, maybe subconsciously, maybe consciously, but now we understand exactly how to select them, how to separate those who have it, those who do not have it. Dmitry had a great message on talent density. Those are important building blocks. Now, about the speed and desire and everything, it's all about also top-down by example. If he's coding, I'm coding. We can demonstrate it. We can show it. The next managers will be coding with Claude Code, with something else, and this will stimulate newer technologies. We also have mandatory requirements for education. Just to continue on this. just to continue on this This is very important comment because one of the key differentiators of the AI agentic engineers is judgment. this is very important comment because one of the key differentiators of the ai agentic engineers is judgment We actually continuously, and this is what Arkadiy Dobkin started to say, we were selecting people with judgment all the time, maybe subconsciously, maybe consciously, but now we understand exactly how to select them, how to separate those who have it, those who do not have it. we actually continuously and this is what arkadiy dobkin started to say we were selecting people with judgment all the time maybe subconsciously maybe consciously but now we understand exactly how to select them how to separate those who have it those who do not have it Dmitry had a great message on talent density. dmitry had a great message on talent density Those are important building blocks. those are important building blocks Now, about the speed and desire and everything, it's all about also top-down by example. now about the speed and desire and everything it's all about also top-down by example If he's coding, I'm coding. if he's coding i'm coding We can demonstrate it. we can demonstrate it We can show it. we can show it The next managers will be coding with Claude Code, with something else, and this will stimulate newer technologies. the next managers will be coding with claude code with something else and this will stimulate newer technologies We also have mandatory requirements for education. we also have mandatory requirements for education If you are not educating, it's a bit of a problem. If you are not educating, it's a bit of a problem. if you are not educating it's a bit of a problem

Speaker 6: Now, going back to the pricing, which I think was your underlying question, seeing where you're sitting and what your role is. I think we are clearly, for this type of skills, we are able to charge higher rates, which actually we talked about it before, that our AI native portfolio drives higher margin. I think it's a continuous moving target because some of these skill sets becoming commodity and as technology rapidly changes. Let's go here, and then we'll go there. Now, going back to the pricing, which I think was your underlying question, seeing where you're sitting and what your role is. now going back to the pricing which i think was your underlying question seeing where you're sitting and what your role is I think we are clearly, for this type of skills, we are able to charge higher rates, which actually we talked about it before, that our AI native portfolio drives higher margin. i think we are clearly for this type of skills we are able to charge higher rates which actually we talked about it before that our ai native portfolio drives higher margin I think it's a continuous moving target because some of these skill sets becoming commodity and as technology rapidly changes. i think it's a continuous moving target because some of these skill sets becoming commodity and as technology rapidly changes Let's go here, and then we'll go there. let's go here and then we'll go there

Speaker 8: Hi, it's Bryan Keane at Citi. Maybe for Larry and Victor, how do you imagine the delivery model in terms of people? Do you need more or less as this evolves over the next three years? Just one for Jason, you know, accelerating revenue growth, given the industry dynamics right now, the question obviously is on visibility. You know, what kind of comfort can you give us in visibility, either contract bookings or when you look out two years, you know, what percentage do you see and how do you get to that number of accelerating revenue growth? Thanks. Hi, it's Bryan Keane at Citi. hi it's bryan keane at citi Maybe for Larry and Victor, how do you imagine the delivery model in terms of people? maybe for larry and victor how do you imagine the delivery model in terms of people Do you need more or less as this evolves over the next three years? do you need more or less as this evolves over the next three years Just one for Jason, you know, accelerating revenue growth, given the industry dynamics right now, the question obviously is on visibility. just one for jason you know accelerating revenue growth given the industry dynamics right now the question obviously is on visibility You know, what kind of comfort can you give us in visibility, either contract bookings or when you look out two years, you know, what percentage do you see and how do you get to that number of accelerating revenue growth? you know what kind of comfort can you give us in visibility either contract bookings or when you look out two years you know what percentage do you see and how do you get to that number of accelerating revenue growth Thanks. thanks

Speaker 21: Yeah, I can start by saying on the more or less, I think the answer is yes, it's both. I think in not only from a geographic perspective, but from a skill set perspective, more of some of these, less of some of those. If you go back to recalling some of the things that Sandra was talking about, the level of data and the signals and the metrics that we track in order to figure out as best we can where we need those people, what skills helps us get a little bit ahead of that curve. I think the other thing that I would say is, you know, we work really hard to put a plan in place every year, and my view is it's only valid for one day, January first. Yeah, I can start by saying on the more or less, I think the answer is yes, it's both. yeah i can start by saying on the more or less i think the answer is yes it's both I think in not only from a geographic perspective, but from a skill set perspective, more of some of these, less of some of those. i think in not only from a geographic perspective but from a skill set perspective more of some of these less of some of those If you go back to recalling some of the things that Sandra was talking about, the level of data and the signals and the metrics that we track in order to figure out as best we can where we need those people, what skills helps us get a little bit ahead of that curve. if you go back to recalling some of the things that sandra was talking about the level of data and the signals and the metrics that we track in order to figure out as best we can where we need those people what skills helps us get a little bit ahead of that curve I think the other thing that I would say is, you know, we work really hard to put a plan in place every year, and my view is it's only valid for one day, January first. i think the other thing that i would say is you know we work really hard to put a plan in place every year and my view is it's only valid for one day january first Because on January second, something has already changed, especially in the market that we're in today and the companies that are gonna win are the ones that can figure that out and pivot the fastest. Because on January second, something has already changed, especially in the market that we're in today and the companies that are gonna win are the ones that can figure that out and pivot the fastest. because on january second something has already changed especially in the market that we're in today and the companies that are gonna win are the ones that can figure that out and pivot the fastest

Speaker 18: For the accelerating revenue, first I'd just start with this year, 2026. With the guide at 3%-6% organic constant currency, you know, our focus is on making certain we can at least hit the midpoint of the range, and clearly we're all driving to achieve something to the higher end of that range. There's already kinda line of sight to larger opportunities that if we can close, and we're trying to close, I think sorta drives us above that midpoint of the range. As I look further ahead, it's the ongoing success with clients. It's all the things we've talked about that clients can't do this themselves. They're increasing dependency on partners like EPAM, but hopefully what we've convinced you of today that this isn't easy and EPAM is extremely well-positioned to participate in these high-growth market opportunities. For the accelerating revenue, first I'd just start with this year, 2026. for the accelerating revenue first i'd just start with this year 2026 With the guide at 3%-6% organic constant currency, you know, our focus is on making certain we can at least hit the midpoint of the range, and clearly we're all driving to achieve something to the higher end of that range. with the guide at 3%-6% organic constant currency you know our focus is on making certain we can at least hit the midpoint of the range and clearly we're all driving to achieve something to the higher end of that range There's already kinda line of sight to larger opportunities that if we can close, and we're trying to close, I think sorta drives us above that midpoint of the range. there's already kinda line of sight to larger opportunities that if we can close and we're trying to close i think sorta drives us above that midpoint of the range As I look further ahead, it's the ongoing success with clients. as i look further ahead it's the ongoing success with clients It's all the things we've talked about that clients can't do this themselves. it's all the things we've talked about that clients can't do this themselves They're increasing dependency on partners like EPAM, but hopefully what we've convinced you of today that this isn't easy and EPAM is extremely well-positioned to participate in these high-growth market opportunities. they're increasing dependency on partners like epam but hopefully what we've convinced you of today that this isn't easy and epam is extremely well-positioned to participate in these high-growth market opportunities If you can be successful in a market that's growing rapidly, that drives higher revenue growth, and that's kinda how I would think about it over the next couple years. If you can be successful in a market that's growing rapidly, that drives higher revenue growth, and that's kinda how I would think about it over the next couple years. if you can be successful in a market that's growing rapidly that drives higher revenue growth and that's kinda how i would think about it over the next couple years

Speaker 24: We have time for one more question. Let's go here. Oh. We have time for one more question. we have time for one more question Let's go here. let's go here Oh. oh

Speaker 29: Thanks for the presentation. Puneet from JP Morgan. It was interesting to see, like, all those, like, the regional heads coming here, like, on the same table in the panel. Talk to us, like, how does EPAM operate across different regions? Is it like? Because, like, the individual regions might have different cultures, like, the policies. Like, is it the same culture, same EPAM across everywhere, same type of people, like, in terms of profile type of people you hire across all regions, or are there differences based on that region's policies or culture? Thanks for the presentation. thanks for the presentation Puneet from JP Morgan. puneet from jp morgan It was interesting to see, like, all those, like, the regional heads coming here, like, on the same table in the panel. it was interesting to see like all those like the regional heads coming here like on the same table in the panel Talk to us, like, how does EPAM operate across different regions? talk to us like how does epam operate across different regions Is it like? is it like Because, like, the individual regions might have different cultures, like, the policies. because like the individual regions might have different cultures like the policies Like, is it the same culture, same EPAM across everywhere, same type of people, like, in terms of profile type of people you hire across all regions, or are there differences based on that region's policies or culture? like is it the same culture same epam across everywhere same type of people like in terms of profile type of people you hire across all regions or are there differences based on that region's policies or culture

Speaker 6: Let me try to start with it. You know, Victor is running a global delivery platform. Basically, he runs the factory itself, right? It's an engine. In this engine, we are enforcing certain level of uniformity, right? What Victor highlighted is the assessment, and basically that's all requirements, how you're going to get promoted. That's the way you are actually being assessed. That's the way you are actually reaching the next level. Is it the same culture? No, because we are coming from different parts of the world. There are unifying elements. There are values which we are sharing. There are ways how we're communicating, and we have to collaborate. We have to work together. We are working together to deliver to one client. Throughout this delivery, we actually kinda syncing up. Let me try to start with it. let me try to start with it You know, Victor is running a global delivery platform. you know victor is running a global delivery platform Basically, he runs the factory itself, right? basically he runs the factory itself right It's an engine. it's an engine In this engine, we are enforcing certain level of uniformity, right? in this engine we are enforcing certain level of uniformity right What Victor highlighted is the assessment, and basically that's all requirements, how you're going to get promoted. what victor highlighted is the assessment and basically that's all requirements how you're going to get promoted That's the way you are actually being assessed. that's the way you are actually being assessed That's the way you are actually reaching the next level. that's the way you are actually reaching the next level Is it the same culture? is it the same culture No, because we are coming from different parts of the world. no because we are coming from different parts of the world There are unifying elements. there are unifying elements There are values which we are sharing. there are values which we are sharing There are ways how we're communicating, and we have to collaborate. there are ways how we're communicating and we have to collaborate We have to work together. we have to work together We are working together to deliver to one client. we are working together to deliver to one client Throughout this delivery, we actually kinda syncing up. throughout this delivery we actually kinda syncing up We have the same values what we're pushing out. We are assessing people in the same way. We're hiring for the same goals and for same profiles with the same criteria. We're running the same process globally, how we run compensation, how we run assessments, how we're going to provide feedback and performance management. It creates one level of sync. Overall, we're hiring engineers, and engineers kinda understand each other and kinda sync on it in a weird way, right? In a geeky way. I think that's who we are. We have the same values what we're pushing out. we have the same values what we're pushing out We are assessing people in the same way. we are assessing people in the same way We're hiring for the same goals and for same profiles with the same criteria. we're hiring for the same goals and for same profiles with the same criteria We're running the same process globally, how we run compensation, how we run assessments, how we're going to provide feedback and performance management. we're running the same process globally how we run compensation how we run assessments how we're going to provide feedback and performance management It creates one level of sync. it creates one level of sync Overall, we're hiring engineers, and engineers kinda understand each other and kinda sync on it in a weird way, right? overall we're hiring engineers and engineers kinda understand each other and kinda sync on it in a weird way right In a geeky way. in a geeky way I think that's who we are. i think that's who we are

Speaker 21: If I could just add on. If I could just add on. if i could just add on

Speaker 6: Absolutely. Absolutely. absolutely

Speaker 21: Sorry. Sorry. sorry

Speaker 6: Go ahead. Go ahead. go ahead

Speaker 21: Were you done? Were you done? were you done

Speaker 6: No, exactly. Go ahead. No, exactly. no exactly Go ahead. go ahead

Speaker 21: No, go ahead. Go ahead. No, go ahead. no go ahead Go ahead. go ahead

Speaker 6: Go ahead, Larry. Go ahead, Larry. go ahead larry

Speaker 21: I think a short way to look at it is globally consistent, locally relevant, and at the end of the day, it's what's best for the client. Client-centric decisions that are locally relevant with the global consistency in processes, culture, core values, but locally relevant is extremely important. I think a short way to look at it is globally consistent, locally relevant, and at the end of the day, it's what's best for the client. i think a short way to look at it is globally consistent locally relevant and at the end of the day it's what's best for the client Client-centric decisions that are locally relevant with the global consistency in processes, culture, core values, but locally relevant is extremely important. client-centric decisions that are locally relevant with the global consistency in processes culture core values but locally relevant is extremely important

Speaker 29: Appreciate it. Appreciate it. appreciate it

Speaker 21: Excellent. Excellent. excellent

Speaker 29: Thank you. Thank you. thank you

Speaker 24: That wraps our Q&A session. I'm gonna hand it back over to FB for closing. That wraps our Q&A session. that wraps our q&a session I'm gonna hand it back over to FB for closing. i'm gonna hand it back over to fb for closing

Speaker 6: If we figure out where the clicker left the building. Who has the clicker? All right. I hope, by this point with the team, we made clear our positioning and why we have the right to win in the AI-native era. I really would like to thank the team itself to make such a great presentation and actually present this message. Our people have navigated technology, social, and geopolitical challenges and changes. We have emerged stronger out of it. We learned a lot, and I think we are the most resilient organization out there, not just in terms of against geopolitics, but any type of technology and social change. Why invest in EPAM? We will be the winners in AI era. We are best positioned to be a leader for enterprise AI transformation. If we figure out where the clicker left the building. if we figure out where the clicker left the building Who has the clicker? who has the clicker All right. all right I hope, by this point with the team, we made clear our positioning and why we have the right to win in the AI-native era. i hope by this point with the team we made clear our positioning and why we have the right to win in the ai-native era I really would like to thank the team itself to make such a great presentation and actually present this message. i really would like to thank the team itself to make such a great presentation and actually present this message Our people have navigated technology, social, and geopolitical challenges and changes. our people have navigated technology social and geopolitical challenges and changes We have emerged stronger out of it. we have emerged stronger out of it We learned a lot, and I think we are the most resilient organization out there, not just in terms of against geopolitics, but any type of technology and social change. we learned a lot and i think we are the most resilient organization out there not just in terms of against geopolitics but any type of technology and social change Why invest in EPAM? why invest in epam We will be the winners in AI era. we will be the winners in ai era We are best positioned to be a leader for enterprise AI transformation. we are best positioned to be a leader for enterprise ai transformation We have the strongest engineering talent or engineering DNA in the industry with a track record of solving our clients' most complex, hairiest problems. We are delivering already AI foundational and AI native work, and it's expanding, and it's growing significantly. We have a clear strategy focused on accelerating and driving profitable growth with margin expansion. Our 2028 goals are accelerated revenue growth, 16%+ non-GAAP operating income margin, and delivering $1.8 billion cumulative free cash flow throughout 2028. Thank you very much. Okay, it doesn't work. As I said to you, the something has to break. Thank you very much for coming. For the audience online, we would like to thank you for attending, and see you next time. Thank you. We have the strongest engineering talent or engineering DNA in the industry with a track record of solving our clients' most complex, hairiest problems. we have the strongest engineering talent or engineering dna in the industry with a track record of solving our clients' most complex hairiest problems We are delivering already AI foundational and AI native work, and it's expanding, and it's growing significantly. we are delivering already ai foundational and ai native work and it's expanding and it's growing significantly We have a clear strategy focused on accelerating and driving profitable growth with margin expansion. we have a clear strategy focused on accelerating and driving profitable growth with margin expansion Our 2028 goals are accelerated revenue growth, 16%+ non-GAAP operating income margin, and delivering $1.8 billion cumulative free cash flow throughout 2028. our 2028 goals are accelerated revenue growth 16%+ non-gaap operating income margin and delivering $1.8 billion cumulative free cash flow throughout 2028 Thank you very much. thank you very much Okay, it doesn't work. okay it doesn't work As I said to you, the something has to break. as i said to you the something has to break Thank you very much for coming. thank you very much for coming For the audience online, we would like to thank you for attending, and see you next time. for the audience online we would like to thank you for attending and see you next time Thank you. thank you