SLB LIMITED/NV — Call Transcript 2026

Good morning, thank you for joining us for SLB's Digital Investor Day. I'm James McDonald, Senior Vice President of Investor Relations and Industry Affairs. This is an exciting time for our industry. Digital is reshaping the way energy is planned, produced, and optimized, and AI is accelerating that shift. At SLB, we operate at the intersection of energy and AI, and as digital scales across the energy value chain, it creates new opportunities for our customers and SLB. Over the course of the morning, you will hear from several of our leaders who will take you through our digital journey, our portfolio, and our strategy, and how this business will continue to support our long-term growth endeavors. We will conclude with a Q&A session, then we will host a lunch, where you will have the opportunity to engage directly with our leadership team. Before we begin, I'd like to remind you that today's remarks will include forward-looking statements. These statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied. The presentations will also include certain non-GAAP financial measures. Please refer to our SEC filings and the materials posted on our investor relations website for additional information. Please note that in the event of an emergency here today, NYSE personnel will be on hand to direct you to the nearest exit and provide further instructions. Let's begin the show. What does it take to shift an industry? It takes vision, it takes capability, it takes the courage to be first. SLB has been shaping the digital backbone of our industry for decades, we've had a lot of firsts. The first to simulate and predict reservoir performance. The first service company to build a global computing network. The first to create software with an open architecture. The first to move upstream platforms to the cloud. The first to drill and steer a well autonomously. The first to deploy agentic AI for upstream operations. Being first is one thing. Going further is another. Going further means building data-driven platforms designed for scale, with insights collected, curated, and connected across operations. Where agents become teammates. Combining domain expertise with digital intelligence. Where equipment is connected, intelligent, and autonomous, where decisions are made with confidence for every well, every barrel, every customer. This is the future we are building, not just as a vision, but as a reality delivered at scale. A future where intelligence is embedded everywhere energy is. Where technology doesn't just optimize performance, it delivers impact. This is how we go further. This is how we lead. This is the next chapter of SLB. Ladies and gentlemen, good morning, and thank you for joining us today. As you have seen, progress in our industry belongs out to those willing to be first, to go further, and to turn vision into reality. That same spirit of innovation is what brings us here today. This morning, we discuss a force that is reshaping how energy is discovered, developed, and produced. That force is digital. For many years, our industry viewed digital as an enabler, a bolt-on tool to improve workflows and to create pockets of value. Today, that has changed. Digital has become foundational. It unlocks performance, efficiency, and returns across every aspect of energy operations. For SLB, it is redefining how we grow, how we differentiate, how we create value. This is not a cycle. It is a structural shift in how this industry will operate. SLB is positioned to lead it. To understand the opportunities ahead, let's begin by discussing the challenge we must address. Energy is the foundation of modern life. Without it, societies cannot prosper, economies cannot grow, and progress cannot be sustained. Yet, as the world enters a new phase of demand, the role of energy is becoming even more important. From advanced manufacturing to cloud computing, transportation networks to AI models, urban growth to national resilience, the modern economy is becoming more energy-intensive. At the same time, expectation around energy are rising. Not only does the world need more energy, it also demands reliability, affordability, and sustainability. To meet this, our industry must achieve new levels of performance and efficiency. This is where digital changes the equation. Digital enables us to produce more intelligently, improving decision-making, automating workflows, and increasing recovery. While energy transformed the world, digital transforms energy. This is the next chapter of value creation in our industry. This is why we have positioned SLB at the forefront. Unlocking the full potential of digital energy requires domain expertise, global scale, trusted relationships, and a digital platform foundation that connects the full life cycle of energy operation. SLB is bringing this capability together in a way few others can. At the moment when the industry needs them most. Today, we're navigating a complex environment, one where energy security has become more critical. Assets are becoming more mature. Customer remains disciplined in how they allocate capital. Against this backdrop, four structural priorities are driving investment across this industry. Improving operational performance, increasing recovery, reducing cycle time, and delivering greater capital efficiency. These priorities are durable, they are investable, and they increasingly favor digital. First is operational performance. Customers need to perform with greater speed, consistency, and precision across increasingly complex operations. That means reducing non-productive time, improving reliability, and using technology to deliver better outcomes. In this environment, operational performance is no longer just a measure of execution. It is a source of competitive advantage. Second is increasing recovery. As the resource base is becoming more mature and complex, more of the next source of value creation will come from existing assets themselves. Customer needs to understand reservoir more deeply, manage production more dynamically, and apply technology that improve recovery over time. It is no longer enough to bring production online. The greater value lies in maximizing recovery throughout the life cycle of an asset. Third is cycle time reduction. Customer needs to move faster from planning to production. From discovery to first oil and gas. This requires technology and workflows that shorten project timelines, improve coordination, and accelerate decision-making across the value chain. The fourth is capital efficiency. Across all basins, our customers remain focused on cash flow and returns. They need more value from every dollar invested, and that requires solutions that improve productivity, reduce total cost of ownership, and deliver measurable impact at scale. Underpinning each of these priorities is a common enabler, AI and digital transformation. Increasingly, this is how performance will be achieved through better data, faster decision, and intelligent automation from planning to production. Customers expect equipment to be connected, workflows to be digital first, and decision to be informed by data. This is why the opportunity ahead is structural. Because even as the market continues to change, the need for energy and returns will not. Digital is key to both. At SLB, we have been helping to shape the digital fabric of this industry for years. That matters because the capabilities our customer requires cannot be built overnight. They need trusted platform, proven workflows, and a partner that can deploy globally. Very few company can do this. We can. Our digital advantage is built across four reinforcing areas. Domain expertise, a platform approach, partnerships, and scale. It all starts with deep domain expertise. In our industry, you can't leave anything to chance. Decisions depend on a deep understanding of physics, the workflows, and the operational constraints. That expertise is embedded in our people, our models, and our platforms. It cannot be outsourced. It cannot be bought off the shelf, and it cannot be recreated by digital-only third-party provider. Second is our platform approach. Products create value, but platforms are what make them scale. In the age of AI, platforms are becoming even more valuable because they are the control layer through which models, agents, and workflows operate together. This is why we have invested in architecture that is open and built to operate in environments our customer manage every day, from subsurface test planning to production operation, and from on-prem to the cloud. This wasn't built in a quarter. It was built over decades, and it is extremely difficult to replicate. Third, our partnerships. We work across operators, technology partners, and geographies to bring customers the best capability of the broader ecosystem to our platform. In digital, no company can do it alone. The key is knowing what to build, where to partner, and how to make those technologies work in the realities of an energy operation. This is what SLB does. We connect leading technology with the data, science, and workflows of our industry to unlock performance and efficiency. Finally, our scale. SLB is funded across the major energy basins with the people, the infrastructure, and operational capability to support customers locally. That matters because digital and AI must work securely and reliably across all assets and operating environment. Our footprint allows us to learn globally, deploy locally, and extend what works across the energy system. This combination is what brings our AI advantage to life. Energy is among the most compelling environments for AI, with complex physics, high-value decision, and vast amounts of operational data. The technology is only as powerful as the data and the domain experts behind it. SLB has a unique ability to bring together platforms, connected assets, partner scale, and deep domain expertise. Individually, this capability matter. Together, they create a differential digital offering that is increasingly important and difficult to match. That is what we bring to our customers, and it is how SLB is taking digital and AI further. What does it mean in practice? It means we can go beyond software, collecting digital intelligence to hardware and sensors in the field so that insight become action and every decision improves the next. This is where science matters, where integration with all key technology makes an impact, and where our differentiation is the strongest. In planning, digital is already accelerating the prediction and improving model quality. AI can create a new growth curve in this market by automating workflows and personalizing our projects as they grow. In drilling, digital is enabling automation and real-time optimization. This lowers cost per mile. It accelerates access to resource, and it can significantly reduce the industry's carbon footprint. In production, digital is increasing uptime by predicting issues before they occur. This cuts maintenance costs and extends asset life. It also optimize the reservoir production potential. These example are here, and they are happening today, and you will hear throughout this presentation this morning. Moving forward, as the industry advance more autonomous operation, customer will simplify who they work with, prioritizing partners who can deliver across the full ecosystem. That dynamic strengthens our core business, creates new revenue opportunities, and expand the strategic value of our platform. This is how digital drives growth, not only within digital itself, but increasingly across all of SLB as we move from being first in digital to becoming digital first. Across every well, every mile, every customer. This is not only a secondary story. It is a growth story. It is a margin story and a return story. Digital is already a powerful earnings engine for SLB. For every $1 of revenue, digital generates 1.5x the adjusted EBITDA compared to the rest of our portfolio. This is also one of the fastest-growing parts of our business, and its margins have continued to expand over time. The value of digital extends beyond the segment itself. This technology are increasingly embedded in the rest of our portfolio, helping customer move faster, produce more efficiently, and recover more from existing assets. When our customer perform better, SLB becomes more valuable to them, increasing retention and expanding our total addressable market. The story is not simply digital as a division. The story is how digital lifts the earnings power of the entire company. This is a far larger opportunity, and today you will hear how we plan to capture it. Throughout this morning, our leadership team takes you deeper into the opportunity, the strategy, the financial frameworks behind this business. First, you hear about our flagship platforms, comprehensive digital offering and competitive advantage. You will see why our position is strengthening as adoption scales and why our platform becomes more valuable as customers move from digital pilots to enterprise-wide deployment. You'll hear about the race to scale digital operation and AI. This is where applications, connected equipment, automation, and AI come together to transform how we sense and manage in real time, and we believe this can become an important new growth engine at SLB. Finally, we discuss key performance indicators. This time, how we are monetizing significant opportunities ahead and share our 2030 financial ambitions for this business. As you listen, I encourage you to keep this in mind. Digital is becoming central to how this industry drives performance, unlocks efficiency, and creates value. With our platforms, domain expertise, and global scale, SLB is well-positioned to lead this next chapter. Thank you again for being here with us. We're excited to share the momentum we have built and the opportunities ahead. Before I welcome Rakesh to the stage, let's hear from some industry leaders as they share their own perspective on SLB's contribution to their digital journeys. In 2019, Chevron, SLB, and Microsoft formed a strategic collaboration to accelerate petrotechnical digital solutions anchored in the Delfi platform. By combining a century of SLB's domain experience with Microsoft's cloud infrastructure and Chevron's experience and operating scale, we've moved from pilot to measurable performance, delivering sustained value across our global operations. Together with SLB's continued commitment to innovation, that's positioned them strongly to build and deploy secure, agentic workflows that are disruptive to our industry. One of the main leverages that we need to use is artificial intelligence and digital. In order to do that, we've decided to partner with SLB on a partnership on subsurface called Arena. It's a 10-year partnership which couples the know-how of our reservoir engineers, along with the digital and AI capabilities of SLB. The SLB Delfi digital platform allows us to seamlessly integrate subsurface evaluation, well planning, and field development, enhancing collaboration, enabling our teams to work concurrently rather than sequentially. As a result, we shorten planning cycles from months to days, significantly accelerating time from discovery to first production. A key part of our 2024 strategy is to implement and maintain world-class standards of operational excellence by embedding digital intelligence with SLB and partners. We are well on the way to achieving this with AI initiatives running across the full E&P value chain. Wow. I've seen this video multiple times, every time I see this video, I feel that we're onto something. What the future holds for us gets me even more excited. Of course, we are very grateful for these messages, and a big thank you to all our customers who challenge us to go further every day. I'm Rakesh Jaggi, and I have the privilege of running the digital business at SLB. Along with Trygve Randen, the Senior Vice President of Digital Products and Solutions, we will highlight SLB's unique and compounding advantage at the exciting intersection of digital and energy. Before I go there, allow me to take you on a tour through the upstream value chain. These are the big questions our customers must answer. We start by asking, "Where should I look for oil and gas? Which basins and geologies offer the best potential for discovery and extraction of commercially viable hydrocarbons? How do I allocate capital across frontier exploration, proven undeveloped resources, and also the aging fields I have in my portfolio? How do I ensure that every asset is producing at its full potential, that I'm leaving nothing in the ground and nothing on the table? Most importantly, how do I operate safely and efficiently across a complex hardware landscape where a single failure can be catastrophic, where decisions cannot be left to chance, because in our industry, probably right is absolutely wrong?" These are some of the questions that define the upstream oil and gas, getting answers to these questions takes us right to the heart of our digital offering. Our ability to serve the upstream market rests on four areas of differentiation. Each of them position us uniquely, but taken together, they represent a wide and deep moat. I know Olivier already introduced these in his opening presentation this morning, but I'd like to take you a level deeper. The first is domain expertise. SLB has spent a century measuring, modeling, and interpreting the subsurface. That science is not peripheral to our digital business. It is the very foundation of it. It is encoded in our software and embedded in the data on which our models are trained. The second is platforms. We have built and commercialized enterprise-grade cloud-native platforms, Delfi for workflows and Lumi for data and AI. These are purpose-built for our industry. They are designed for the specific data types, security and uptime requirements, and scientific workflows that the upstream operators depend on. Trygve will give you a more in-depth look at our technology stack and why is it that it is so special. The third differentiation is partners. Our platforms are open and host a best-in-class tech ecosystem. We are deliberate about what we build and what we integrate. Cloud infrastructure from the leading hyperscalers, operational data capability and AI tooling from specialized technology players, large language models or LLMs from leading AI providers. Our platforms are enriched by the technology of others in areas where we choose not to compete. You will hear directly from some of these partners in a bit. The fourth key area of differentiation is scale. In many ways, it is the outcome of the other three. Domain expertise gives us the right to play, platforms give us the means to deliver, partners give us the speed to market, scale allows us to deliver for our customers across all geographies and resource plays. These four areas, domain, platform, partners, and scale, are mutually reinforcing. They allow us to compete in a way that other technology companies or traditional oil field services and equipment companies cannot. All of this did not happen overnight. SLB has a history of disruption embedded in our DNA. We began collecting computer-ready data in the field in 1952. Since then, we have seen a succession of technology shifts from mainframe to workstations to personal computers, then onto the cloud. With each of these shifts, we deployed the same playbook. Each time a new computing architecture emerges, we use it not only to modernize the existing tools, but to fundamentally expand what our customers can do. Another shift is underway, this, ladies and gentlemen, is truly different. Artificial intelligence isn't just changing how software is delivered and consumed. It promises to be the most fundamental and revolutionary shift we've ever seen. agentic AI, in particular, changes what software can do. With agentic AI, we are creating systems that observe, reason, act, and learn. Dare I say that while others have been fast followers, when it comes to our digital capabilities, we've always been first. Just two weeks ago, as some of you would have noticed, the AI-Driven Enterprise Institute awarded SLB a perfect score for AI adoption. A score achieved by only three other companies, NVIDIA, Amazon, and Meta. We are a company whose entire digital history has been converging on this moment, where domain science, trusted data, and intelligent systems meet in a single stack. I want to give you an analogy. The banking sector has undergone a very similar journey. The way my father banks, and God bless his soul, he's going to turn 92 day after tomorrow, and the way I bank are very different. The banking sector, three to four decades ago, decided to digitize each of the steps that required a customer to visit the bank. I don't remember the last time I went to the bank. This is exactly what we have done for our industry. Let me illustrate how our domain applications help our customers along the industry value chain, just like the banking sector. All of our domain offerings can be classified in two broad categories: planning and operations. There are steps that you have to take to get to your destination as a petrotechnical or operational expert. We have a product that will help our customers perform each of these steps digitally. We do not want them to work manually like my father did decades ago. They never have to bring manual skills to bear if the job can be done successfully, more efficiently, and more accurately by software. Let me go through the steps a petrotechnical expert undertakes in the planning phase. The workflow in planning begins with raw seismic data. This is the aggregation of sound waves that are sent into the Earth and reflected back. It's transforming billions of acoustic signals into a usable image of the subsurface. Think of it like the MRI scan of the Earth. Geophysical interpretation maps the layers and faults. Structural modeling and well interpretation then reveal how subsurface layers were formed and enable us to construct a 3D model of the subsurface. Reservoir and geological modeling predict properties like porosity and permeability and identify where hydrocarbons are likely to accumulate. Reservoir engineering quantifies the flow of fluids through rock formations and how the field will produce over time, incorporating the surface infrastructure into that equation, too. Next, field development planning or FDP comes in. Every technical step is overlaid with economic considerations, oil prices, capital outlay, operating costs, each element with its own uncertainties. Field development planning determines the returns to access the hydrocarbons underground. What you've just seen is a whirlwind tour of what a petrotechnical expert lives daily. We have an application for each of these steps. Omega, Petrel, Techlog, Intersect, FD Plan. These offerings enable our customers to complete their work anytime, anywhere, across every stage of the planning process. Once a development is sanctioned, the focus must shift to operations. Drilling planning is where operators engineer the well that will access the reservoir, defining trajectory for every section of that well. Drilling operations is execution of that plan, managing the real-time complexity of putting a wellbore through thousands of meters of rock. Production operations is the management of flowing wells and production networks. It includes the optimization of hydrocarbons to the surface. For aging fields with declining pressure, artificial lift is employed. Asset performance then encompasses the surface infrastructure, including facilities, processing equipment, pipelines, et cetera, that must operate continuously because unplanned downtime has consequences measured in millions of dollars a day. What we just saw is a quick tour of the operations. DrillOps, OptiFlow, OptiLift, OptiSite, powered by our Agora edge AI platform. Just as in planning, SLB Digital is increasingly serving each of these core operating processes, too. We are uniquely present across the entire value chain, from exploration through development and production, both in planning and operations from the edge to the office. I'm sure my daughters would like to bank differently compared to me, and we too are preparing for the agentic AI future for our industry. Besides planning and operations, we also have a market segment of data and AI. This framework on the slide now will provide insights into a key part of our digital strategy. If planning and operations are where the decisions are made, the data layer is where the raw materials for those decisions is organized and made accessible. Upstream operations generate extraordinary volumes of data. A single deep water well through its lifetime will generate around 10 petabytes of data, which is equivalent to nearly half a million of the 4K movies that you and I enjoy. This is a distinct and new market with new buyers for us. I've described planning and operations as two different worlds. As many of you would have already guessed, there is huge value in bringing them together, our digital tools make that possible today. Connecting these worlds for data is what SLB's Lumi and data and AI platform makes possible. It is a single trusted layer which connects planning data to the operations data seamlessly. Just like the banking sector, the Delfi platform has digitized the workflows for both planning and operations on the cloud. We are the only company that plays in all three of these market segments, planning, operations, and data and AI. The value we generate is clear. In planning, we reduce cycle time and risk. In operations, we enable greater production and superior efficiency. With Lumi, we help unleash the power of AI. Data from operations helps us plan better, which optimizes future operations. This becomes an exponential loop, bringing significant improvements in efficiency. From a commercial perspective, this is the flywheel that drives our commercial model too. More integrated workflows means more platform usage. Richer data means more AI workloads. Better AI means customers do more analysis, run more scenarios, deploy more agents. The circle turns, and with every rotation, the outcomes improve for our customers, and the value of our partnership deepens. Finally, let me put this in a context that will speak to all of you. To illustrate this, I will use Microsoft's product architecture as a comparison. We all know about the Microsoft stack, with tools like Word, Excel, and PowerPoint. You're also aware of the OneDrive and how you access and share files in your organization. Petrel, Techlog, DrillPlan, and OptiFlow are applications just like Word, Excel, and PowerPoint. Delfi is the Office 365 equivalent that binds them together architecturally and commercially in a cloud-native digital platform. It is the environment which our planning and operation software is accessed. Petrel, Techlog, DrillPlan, OptiFlow, all delivered through a single secure experience. Delfi is more than a hosting layer. It is an integration environment, the place where decisions flow between disciplines without manual handoffs. A subsurface model built by a geoscientist in Petrel can be consumed directly by a drilling engineer in DrillPlan. Real-time production data in OptiFlow can feed back into a reservoir simulation in Intersect. The transition from planning to operations that we described earlier, that seamless handoff between the work of deciding where to drill and the physical work of actually drilling that well, Delfi is where that becomes real. Lumi is our data and AI infrastructure, just like OneDrive and Azure AI Foundry is for Microsoft. If Delfi is where workflows run, Lumi provides the scalable, governed environment to ingest, contextualize, and deliver the data so that the right data in the right shape reaches the right workflow at the right time. It is also the home of our agentic AI workflow. We have things like domain foundation models, our agentic AI framework, and digital twins as a part of it as well. Working in sync across both Delfi and Lumi is Tela, our agentic AI, the parallel is Copilot in Microsoft. Shashi will elaborate on this exciting technology later. Briefly put, Tela is an agentic AI mesh that operates within the workflows and data environments our customers already use. Its architecture follows a continuous loop: observe, plan, generate, act, and learn. It is grounded in domain models and industry-specific guardrails that SLB has built. Before I hand it to Trygve to share more details on our platform approach, let's hear from a key customer in the Middle East. At the core of ADNOC's subsurface AI strategy is ENERGYai, which brings agentic AI into upstream workflow. Built with technology partners, including SLB, ENERGYai uses digital platforms, including Lumi and Delfi to enable integrated workflows and accelerate deployment at scale. This represents the world's first private cloud deployment, enabling intelligence and integrated workflows across the enterprise. Starting with 42 agentic AI-driven subsurface use cases, spanning from seismic interpretation to reservoir simulation, ADNOC can accelerate reservoir understanding, enhance field development planning, and identify new resource opportunities. For productions and operations, the strategy is driven by AI PSO, delivering more than 25 connected workflows that enable smart, autonomous operations. These capabilities support greater operational efficiency, improved decision-making, and increased performance at scale. The opportunities ahead are significant, and together with technology partners like SLB, we are well on our way to meet our ambitions. Congratulations to SLB on 100 years of leadership and innovation. We are proud of our partnership and excited about what the future holds. Shukran, Ali, and thank you, Rakesh. The SLB's platform approach has been a cornerstone of our digital strategy for over two decades. To start, it's worth grounding what we mean by platforms because the term can be used loosely. Our platform must do two things, provide and make an enterprise trusted data available and accessible And provide an open environment in where that data is consumed by applications, by workflows, and increasingly, by AI. It is the layer that makes everything work together at scale. In our industry, that bar is unusually high. As Rakesh explained, data in our industry is complex, domain-specific, and often business and safety-critical. The workflows span multiple scientific and engineering disciplines. The operating environments are global and frequently constrained by data residency and increasingly, technology sovereignty constraints. A horizontal multipurpose cloud platform does not meet these needs. What is required are platforms built for the domain that understand the data, understand the workflows, and can operate at enterprise scale for the most demanding customers. Our customers operate in a world of multiple vendors and proprietary data. We accommodate customers who wish to bring their intellectual property and run it alongside ours in a governed environment. We even partner with many of our customers to co-develop technology. Through open APIs and an extensible application framework, a concept we pioneered 20 years ago with the industry's first open API and plug-in environment, customers and third-party developers can deploy their own technology, their own algorithms, alongside ours in Delfi, Lumi, and Tela. They bring their workflows, we provide the platform. Turning to security, our platforms operate under the tightest standards with data encrypted in transit and at rest, multi-factor authentication, and role-based access control. For an industry that deals in competitive sensitive data and that operates under regulatory oversight, this is not a feature but a prerequisite. There is no doubt we have the data, but one of the structural constraints that has held this industry back is the physical limitations of traditional computing infrastructure. Our reservoir simulation that takes three weeks to run on a workstation can run overnight using elastic cloud resources. A seismic processing job that would require a dedicated data center can be scaled on demand and released when complete. Lumi provides scalable storage and governance for petabytes of operational and subsurface data. Delfi provides on-demand compute for simulation, processing, model training with no ceiling and capacity. The shift from evaluating three development scenarios to evaluating 300 has a dramatic impact on our customers' understanding of development risk, and is only possible when compute is no longer the constraints. Our platforms remove that constraints. Rakesh has explained Tela and the domain foundation models within Lumi, but it is worth stating plainly what this means. Every agentic AI deployed in this industry depends on the quality of the models, the quality of the data on which these models are trained, and the quality of the domain science that governs their output. We have all three. Our models are trained on all that we know and allow our customers to enrich them with all that they know. They are grounded in physics, not just pattern recognition. They are deployed within an agentic framework that can act, not just advise. When we describe our digital platforms, we are describing something quite specific. Not a collection of point solutions, not desktop applications moved to the cloud. An integrated open platform environment underpinned by the industry's deepest data architecture, powered by domain-native AI, and designed to serve the full life cycle of an upstream asset. There is no other platform in the energy industry that offers this combination of workflow depth, data breadth, domain intelligence, extensibility, and enterprise-grade infrastructure. That is the position we have created, and it is the position we will extend. The final aspect is our partner ecosystem. Let me dive deeper into that. I should be clear that we did not build all of this alone. We have more than 40 strategic partners are contributing capability across our platform. I will talk about them in a moment, but the ecosystem extends well beyond our strategic partnerships. More than 175 commercial plug-ins are available on our platforms. Developed by third parties who are built on our open APIs and frameworks, and more than 110 third-party applications are hosted on the platform, accessible to our customers alongside our own. This matters for two reasons. First, it is evident that openness is a reality, not just a philosophy. Developers and technology companies are investing their own money and resources building on our platforms because the customer reach, the data environment, the commercial opportunity justify that investment. That is the hallmark of a genuine platform ecosystem. Second, it deepens the moat. Every third-party application, every partner integration increases the value of the platform. The ecosystem compounds our own investments and makes the platform more valuable in ways we do not have to build or fund ourselves. In addition to the other vendors who have brought their IP to our platform, our strategic partner ecosystem above that network is structured in six layers, each serving a distinct function in the platform. We have foundational partnerships with AWS, Google, and Microsoft, the hyperscalers. They are drawn to us as the market leader in the domain, and we are drawn to them for their modern cloud infrastructure on which Delfi and Lumi run. Multi-cloud support is not a convenience but a requirement. Our customers operate all over the world, many with strict data residency constraints. Being cloud agnostic means we can deploy wherever the customer needs us. We can also deploy on the edge using our Agora edge AI platform. Agora addresses the real-time demands of remote environments where connectivity, latency, cybersecurity, and operational continuity affect performance. I won't expand upon the other layers in this. The point is not the number of logos. We could have added many more. It is the architecture. Every layer is deliberate. Every partner is best in breed in their domain, and together they create a platform that is comprehensive without being closed. Let's hear from some of these valued partners. Microsoft and SLB have worked together for decades, evolving alongside some of the biggest shifts the energy industry has seen. That collaboration sets the foundation for how we work together, combining deep domain expertise with powerful platforms. As SLB enters its second century of technical leadership, Google Cloud is ready to anchor your vision with our own pioneering investments in advanced energy. Together, SLB and AWS are building the digital backbone so our joint customers can perform at an AI-accelerated level. We are entering a new industrial era powered by AI, and energy sits at the center of it. We focus very strongly on strategic partnerships like the one with SLB. SLB brings digital and domain expertise across subsurface, subsea, and topside production systems. 80% faster in competition cycles, earning success rates that are changing the economics of natural assets. Together, we deliver grounded real-time insights that drive action. One joint customer of ours increased production by 100,000 barrels and also saved $4.3 million in operating expenses. Together, we are creating a foundation that helps SLB move faster, operate smarter, and deliver more value to customers around the world. Quite some heavy hitters that gave their video statements there. I want to emphasize on something that comes from these videos, and that is one of the most significant barriers to entry in our industry, trust. Our customers trust us with their most competitively sensitive data. Seismic surveys that cost hundreds of millions of dollars to acquire. Reservoir models that underpin the multi-billion development decisions and real-time operational data from producing assets. This is data that governments regulate, that boards scrutinize, and that our customers' competitors would love to see. We deliver our trusted platforms across more than 80 countries, essentially everywhere that oil and gas is found. Each with its own regulatory framework, its own data and technology requirements, and in many cases, its own constraints on which cloud infrastructure is permissible or even available. Solving for all these constraints at scale requires multi-cloud deployment capabilities, on-premise options, and a deep operational understanding of the legal and political landscape in every market we serve. A national oil company in the Middle East has fundamentally different requirements from an independent operating in the U.S. or a multinational operating in deep water Brazil. We serve all of them, whatever their infrastructure constraints. In addition to sovereignty, reliability reinforces our customers' trust in SLB. We are well in excess of 99.5% uptime. In many cases, we continue delivering our services even when the hyperscaler goes down. It is possible precisely because we operate across multiple cloud providers. If one goes down, we move over to another. Our customers' workflows do not stop because a data center in a single region has an outage. For an operator running real-time production surveillance or time-critical drilling operations, that resilience is a condition of adoption. If trust is the foundation, scale is the outcome. A scale we have achieved thanks to more than $3 billion of R&D spend since 2016 and 390 digital U.S. patents granted in the last five years. That scale of what we have built is worth dwelling on for a moment, because these numbers are not projections, they are the current state of the business. At the center of this slide, more than 90% of global production is simulated or modeled using at least one of our digital solutions. I'll let that sink in for a moment. That is not a market share statistics, but a measure of how deeply embedded our technology is in the decisions that Rakesh talked about that govern the hydrocarbon output of the world. Around it, the operational footprint. More than half a million feet drilled each quarter using SLB automation technology. Over 2 billion API calls across the platform in 2025, a proxy for the volume of machine-to-machine interaction, executing continuously across our infrastructure. Over 45 million CPU hours in Q1 of this year alone and growing as customers are unlocking the simulation processing and AI workloads we discussed earlier. Supported by over 2,600 petrotechnical experts, the largest team in the industry. The position is built. The question is now how fast and how far we can grow from it. Well, let me hand back to Rakesh to describe the market opportunity. Thank you, Trygve. I would now like to define and quantify the market we play in, ladies and gentlemen. This chart from Gartner shows the digital spend as a percentage of the total expenditure across major industries. Oil and gas digital spend, 4%-5%, considerably less than manufacturing and natural resources that you might expect to closely correlate. The point is simple. Oil and gas is one of the most data-intensive, technically complex, and capital-heavy industries on Earth. Yet it spends proportionally less on digital technology than almost any comparable sector. However, this is not a market where we are merely fighting for a share of a fixed pie. The pie itself is growing, and it is growing because the industry is underinvesting relative to its complexity, and the technology to close that gap now exists. Less than half of that investment supports the technical workloads that we've been talking about this morning. That is where we play and where emerging tech disruptions will bring significant value to our industry. According to Rystad Energy, this market in 2025 represented about $25 billion. Looking at the breakdown of this digital TAM, customers are allocating digital spend across planning and development, operations, and their enterprise digital infrastructure. Furthermore, the capabilities I've been talking about have only recently matured to the point where they will become compelling. For us, this means the total addressable market has significant room to expand. Another way to look at this market is through the lens of the main player in this TAM. On the top right here are the traditional oilfield services and equipment competitors. They compete with us in domain-specific software, particularly in planning and drilling. We are unmatched in our investment in platform modernization and in artificial intelligence. Next, the industrial technology companies. These are very credible players in operational technology, particularly in surface automation, process control, and equipment monitoring. They bring strong capabilities in the industrial IoT and facilities layer. We compete with them in operations. They lack subsurface domain expertise. The enterprise technology companies, which serve the industry's broader IT needs, networking, databases, communications infrastructure, et cetera. They operate horizontally across many industries, but without domain specialization. The system integrators. These firms provide implementation services, custom development, and data migration. They compete with us in services around the data, but they do not own platforms, domain science, nor proprietary AI models. We have the hyperscalers and horizontal platform providers who bring cloud infrastructure, compute, and data storage. They are essential to the ecosystem, but they are not competitors in the domain software. As we've described, many are already partners providing the infrastructure on which our platforms run. We are the only company equipped to address a majority of this market. Rather than competing with the hyperscalers and system integrators, we have made them a part of our architecture. Their infrastructure powers our platforms. Their compute is used to fuel our AI models, and their services assure rapid market adoption of our platforms. In other words, we convert potential competitors into distribution and capability partners. On the other side, our open platform architecture means the technology of others can integrate into our environment. We do not require the customers to choose between us and these companies. We provide the platforms on which they coexist. Other companies occupy a segment, we occupy the entire space, more than two-thirds of the market. Our openness turns these companies into participants in our ecosystem rather than obstacles to our growth. I now want to spend a few minutes talking about how this market is expected to evolve. By 2030, the expectation is that another $10 billion in annual spend will be added as digital spend becomes further decoupled from the overall industry CapEx and OpEx. This growth is driven by our customers' ambition to secure greater value from digital, especially in operations where significant value is expected. You will hear more about this in the next section. The most important number is the one on the top right. With accelerated AI adoption, the total market could reach as much as $50 billion by 2030. This reflects what happens when AI fundamentally changes the nature of digital work. When interpretations become exponentially faster, customers do more of them. When simulations are no longer constrained by hardware limitations, teams run hundreds of scenarios instead of just a few. When agentic workflows automate routine surveillance across thousands of wells, digital spend expands. It does not just make existing work more efficient, it unlocks possibilities that were previously uneconomic. For us, this is the most important dynamic. We are not competing for a larger share of a static opportunity. The opportunity itself is accelerating, driven by the same AI capabilities that we are building into our platforms. That, ladies and gentlemen, is our digital advantage. With that, let's now zoom in onto two parts of this market that are growing the fastest, digital operations and AI. These will unlock the possible doubling of this market. You're about to hear from Cecilia and Shashi, who will share how our digital capabilities are transforming operations and how AI is expected to disrupt our industry. Before Cecilia takes the stage, let's hear from a few more of our customers. Thank you. Our digital collaboration with SLB brings together deep domain expertise, scale, and capability to address the specific challenges across the subsurface, well construction, and production. Through this collaboration, we have strengthened our ability to understand subsurface complexity, optimize drilling, and make better decisions faster. Analysis that previously took months can now be completed in weeks or even days. With SLB solutions, particularly OptiFlow, OptiSite, and Agora, YTS will comprehensively optimize production and the facilities, improving performance, efficiency, and operational integrity. We are now building on this strong foundation by expanding our collaboration into production, including the pilot of AI-driven tools for real-time optimization. We deploy SLB technology on the majority of our wells through artificial lift data transformation, through chemical data transformation. While that process has often been manual in how we optimize, we're starting to breach the world of automation and machine learning. We implemented the SLB Agora solution as a pilot approximately six months or so ago, and we saw an immediate 15%-20% uplift relative to how we were doing it. Delfi has become the platform on which we bring new technology into our subsurface workflows. We keep adding these features to our main process, which means we are able to work together more easily, grow as needed, and deliver more value across the company. Thank you, Rakesh. I'm Cecilia Prieto, what I'm going to do today is to take you to the physical world, where digital meets operations and delivers results. Our industry is very clear about where we're going. Autonomous operations. That's the destination. The challenge isn't the feasibility. We've already proven that autonomy works. The question is, how do we scale? This can only happen when we are applying digital in every operation. In the next few minutes, I'll tell you how digital has a material impact on our customers' production and lifting costs, and why SLB is best positioned to truly transform the way it is done today. To understand what we can offer and how fast we're scaling, let's take this story from the beginning. We have a vast footprint of services and equipment in the field delivered by our reservoir performance, well construction, and production system divisions. This is our sandbox. Our first step is to connect this footprint. That's how we collect data and enable surveillance and control. Our customers pay for this value. Here's just one of many examples. Today, 35% of our electrical submersible pumps are connected and monitored. By 2030, we aim to reach 60%. The next tier is intelligent solutions and services. This is where operational data is turned into actionable insights. Another example, today, about 14% of our formation evaluation operations run with a digital insight add-on. By 2030, our ambition is to drive 60% of adoption amongst our customers. The final destination, autonomy. It is not a dream. It is happening today. 3% of the footage we drill is done autonomously. By 2030, we aim to reach 25%. This is the most advanced form of digital operations and where the industry will unlock the biggest value. Here's the reality. Drilling a well is extremely challenging. The wells we drill keep getting longer, and our reservoir targets are miles and miles away from the wellhead, with lots of unknown on the way. Unknown rock properties, unknown pressure levels, unknown fractures, porosities, and so much more. Every day, something goes wrong. The industry wastes about $4 billion every year to remediate high-impact events. It can take a few days or even a few weeks to regain control and resume operations. Complexity is multiplied because drilling involves several service companies and rig contractors spanning many individual workflows. Two decades ago, we began digitalizing drilling by collecting and interpreting data in remote operations centers where SLB and our customers work side by side. We needed less personnel at rig sites, preserved key expertise in those centers. Until recently, manual lab measurements and Excel files were still the norm. Directional drillers, subsurface experts, and fluid experts were all each receiving more data to interpret and act on. It was a step forward, but they were still working in silos. More integration was needed. That is exactly what we did. We integrated the data and workflows into what we call drilling insights. They provide intelligent recommendations in a standalone workflow or across multiple ones, and this is where we generate 80% of our digital drilling revenue today, on top of SLB drilling services or as a generic application. Here comes the big finale. When we combine drilling insights with bottom hole and surface automation, drilling autonomy becomes a reality. The most optimal decisions are recommended and executed in real time by the system without slowing drilling down. Many decisions can be taken and executed simultaneously. This is simply not humanly possible. Drilling autonomy is how we drill wells faster and better, always placing them in the production sweet spot. It's how we improve drilling efficiency by 25%-40% and help our customers produce more and reduce lifting costs. Let me tell you about a real example. In Libya, we have been working with Sirte, a subsidiary of the National Oil Corporation. To accelerate well development, autonomous drilling was the answer. Today, Sirte produces around 110,000 barrels of oil per day with ambition to increase this further and fast. This is critical to the country's national production and economical development. We deployed DrillOps automation with all the drilling insights, orchestration, autonomous well placement, and bottom hole automation for directional control. Here, the autonomous drilling system decides on all directional changes to remain in the best zone of the reservoir, all while optimizing speed and safety parameters. It only needs 15 seconds to interpret data, decide to change the drilling plan, and send the change command to the bottom hole assembly. All of this would have taken 45 minutes without automation. If you were drilling at 100 feet per hour, it took 75 feet before the course of your well could be updated. It's like missing your exit when driving at full speed on the highway and only realizing it miles later. Tela, our agentic AI assistant, is already embedded in the system to help users who may decide to go back to manual mode. Here are the results. We doubled drilling efficiency and placed the well 100% in the reservoir. Our preferred monetization for a full drilling autonomy project like this is a performance model where we capture a portion of our customers' cost savings. As you can imagine, the revenue impact can be meaningful. In 2023, SLB was the first company in the world to drill a well with autonomy in Brazil. We could only deploy drilling autonomy on rigs equipped with our own control systems. To scale, we needed to develop interfaces to enable connections to a wide range of rig control systems. That is why we partnered with rig companies such as Nabors and H&P for land rigs, and Transocean and NOV for offshore operations. Thanks to this, we have the potential to automate 25% of rigs worldwide today. By 2030, we will be able to connect to 85% of the rigs. Today, we drill autonomously for 15 customers in every type of environment and geography, and we hold the most patents by far. We continue to innovate our drilling assemblies to bring new levels of control, precision, and speed. Speaking about the value we create for our customers, let's hear from one of them. Today, we operate in an increasingly complex environment with growing challenges across assets and geographies and higher expectations of safety, efficiency, and performance. In this context, delivering reliable, affordable, and sustainable energy is our priority, technologies plays a key role in making this possible. Digital solutions, data, AI, and automation help us simplify complexities, improve decision-making, and accelerate execution. Technology alone is not enough. Strong partnerships are essential, SLB has proven to be a strong partner for Eni across multiple areas. Drilling is a clear example. By adopting a digital drilling model built around the SLB solution that integrates planning, real-time execution, and automation, we achieved up to 35% reduction in drilling time with safer and more predictable operations. In Congo, this approach enabled us industry-critical level of full drilling automation. We also deploy a wider set of SLB applications across the value chain, from retrievable ESP system in Mexico with reduction of downtime and cost savings, to the application of geosteering technologies in Ivory Coast to navigate within the reservoir formation and maximize well productivity. These results show how the pragmatic use of technology and innovation at scale, combined with trusted industrial collaboration like the one we have with SLB, create tangible and measurable value today and open the way to further joint opportunities across new development areas. Hearing from one of our major customers talk like this about our collaboration makes me very proud, I really look forward to seeing what else we can achieve together in the drilling space. Now, let me take you to the world of production. Complexity is heightened here. We battle disconnected equipment installed by different companies across multiple decades. A lot of it is still analog. This fragmented physical reality is found at the well level, across surface, production systems, along pipelines, and in facilities. The monitoring process will require a human to travel to the field to collect measurements. This is why connectivity is the foundation. It enables basic surveillance that generates data from SLB equipment or other providers' hardware. That's how we bring production into the digital age. Once the data stream is enabled, we can optimize equipment with digital twins. We combine physics-based models with AI and our domain intelligence to identify equipment constraints sooner and deliver real-time insights to take the right action at the right time. This means more equipment uptime, leading to more production. Going further, digital enables optimization at a system level. It breaks the silos between all the equipment that coexists in a production operation, and finally connects all the elements from reservoir to point of sale to maximize production and ultimate recovery. Just like drilling, production is moving towards full autonomy, where technology not only informs intelligent decisions but also makes them. Imagine a production agent that is scanning equipment operating parameters continuously. Imagine how it could intuitively understand the impact a single change has on the entire production system. It acts autonomously and ensures that a single set point optimization continues to trickle through the production system to optimize it entirely, from reservoir to wells to surface equipment, pipelines, and to facilities. It sounds simple when you say it like that, but in fact, it's a very highly complex multivariable and cross-domain workflow. This is what we're actively working towards. This future is not so far ahead of us. In the U.S. Permian Basin, all wells are equipped with pumps that help lift oil to the surface. Production can decline rapidly due to the dynamic reservoir changes, and as a result, operations require continuous monitoring of artificial lift equipment. We worked with a major operator to provide real-time optimization recommendations that can be deployed on SLB and other providers' electrical submersible pumps. These recommendations are transmitted instantly to their innovative closed-loop control technology. The system was deployed on an initial 26-well pilot. It continuously monitors well conditions, generates optimal operating set points, validates them, and implements the adjustments in a fully automated cycle. Full optimization, which initially took 29 days manually, was cut down to three days. That's 90% improvement. Equipment downtime was reduced by half. Working hours needed to monitor wells and optimize them were significantly reduced as well. Production per well was increased by 10% based on Permian average. After the success of this pilot, we signed a three-year enterprise agreement with all of the Permian ESPs and to monitor all the other lift systems in the U.S., including the gas lifts, plungers, and rod lift systems. As of today, 800 wells are actively using this closed-loop system, and we're running surveillance and optimization workflows on their 11,000 wells in the U.S. With the integration of ChampionX, we expanded our reach with the additional footprint of production equipment. Today, our install base includes 200,000 physical equipment that is either already connected or can be in the future, from artificial lift systems, which we talked about, to flow meters, chemical tanks, processing equipment, well heads, and completion hardware. All of this is our initial playground to deploy more digital production solutions. We're on a clear path to scale and this SLB install base and beyond. Looking at production and system optimization, I would like to talk to you about a digital solution we're very excited about. It truly showcases we innovate every single day. We built our existing OptiFlow tech offering, which unifies reservoir and wells into a single intelligent ecosystem to create a module exclusively available on our intelligent completion hardware. We're piloting it with three of our largest customers in deep water West Africa, in the Middle East, and the Caspian region. What we give them is production insights they would not have dreamed of before without overengineering their completions. Customers can see water or gas breakthrough data in real time and zone-by-zone productivity index. With the active inflow control provided by our electrical completions, which are the higher tier of our intelligent completions, they can act on these insights immediately. Production is optimized in minutes by closing, opening, or regulating from individual producing zones, all without additional intervention or workover. No more guessing and waiting, which often results in production loss. For high-producing wells like deep water wells, it promises to be a game changer. It's like wearing a smartwatch and continuously monitoring your heart rate and blood pressure, getting alerts and recommendations without having to go and see a doctor to get your ECG measured. OptiFlow is patent protected. It is one of a kind because it leverages our production domain understanding and digital expertise combined with truly differentiating completion equipment. Simply put, it will be hard for our competition to replicate. According to Kimberlite research, the intelligent completion market will double in the next two to three years. SLB will quadruple installations of electrical completion specifically. Amongst our top 15 completions customers, eight of them have already adopted them with immediate reservoir control benefits. Our mission is to upsell OptiFlow on more than 80% of our electrical completions, and we know we can do it because from early pilots, all customers have already signed the subscriptions. Traditionally, operators follow a longer adoption path from proof of concept to proof of value before committing to long-term commercial contracts. The speed of adoption we are seeing with OptiFlow is unprecedented. After all this, what are the key takeaways? It's that SLB has a unique advantage to capture the rapid growth in digital operations, and this is why we're confident. First, we have the industry's broadest operational footprint across all key environments and geographies. Every year, we drill or complete 20,000 wells, execute 100,000 intervention operations, and install more than 8,000 ESP pumps. Every drilling or production operation is an opportunity to introduce and upsell a digital solution. Second, SLB has a technology portfolio no other company in the sector can replicate. From our physical products and services to our digital platforms and solutions covering all the industry workflows. Third, we leverage our digital platforms. All our digital operation solutions run on Delfi. It means that they inherit robust cybersecurity standards, cloud integration, data management, and a common edge infrastructure. This speeds up deployment and provides the foundation to scale AI in all our operations. Finally, we never stop innovating. Our process is symbiotic between innovation in hardware and software. Innovation projects are often linked, as we demonstrated with the intelligent completions example. As the digital operations mature and ingest more data, our systems are getting more intelligent. Our leadership position gets stronger, and the gap with our competition widens. The race to scale is on, and we are leading it. Let me hand over to Shashi, who will tell you more about AI, its transformative power, and where our growth efforts are focused. Thank you. Every molecule of oil and gas ever produced began with a question about what lies beneath the surface, answered with incomplete data, fragmented visibility, and the limits of human know-how. The industry spent decades digitizing and built real value doing it. The tools it built, the workflows, the simulations, the data systems, were designed to support decisions, not make them. They capture. They store. They model. What has been missing is the intelligence layer that connects insight to action. Agentic AI continuously reasons, interprets, and responds subsurface to surface, grounded in the physics of the domain. What once required weeks of specialist analysis now happens in hours, not by replacing expertise, but by extending it across every well, every facility, every enterprise. This only works if the AI thinks like the industry. Platforms have to be purpose-built for that trusted data, domain foundation models, and decades of industry expertise. AI that talks like an expert and analyzes like an engineer. The result, every reservoir, every well, every pump, every facility continuously optimized. When conditions change, the system responds. Operational costs no longer scale with complexity. Assets run around the clock, proactively managed, continuously learning. The future belongs to those who add intelligence to what they've already built. We're already leading the way. Thank you, Cecilia. Good morning, ladies and gentlemen. I am Shashi Menon, and I lead digital technology development for SLB. Rakesh and Trygve have outlined our platforms and our market opportunities. As Rakesh was looking back through our digital history, it reminded me of my own digital journey at SLB. I had the opportunity to lead the development of our first digital platform around Excel, GPU computing with NVIDIA, cloud computing with Google, and data platforms with Microsoft. Now here I am to tell you what we are doing in this exciting world of AI that we are all living in. Today, I'm going to show you our proprietary AI technology stack. I will tell you why this is entirely unique, how we have developed specialized domain foundation models, and the secret behind why nobody else can replicate this. Let's get going. The foundation of our AI capability is an industrial platform configured specifically for the physics and data complexities of the energy sector. These are the three key elements that I want you to take away. I can tell you that these three elements are unique in our industry. No one has been successful in building these to date, not just in our industry, but across any industrial sector. They are the ones that will make or break AI in our industry. Let me explain each of these three pillars and show you how they will drive our AI transformation. Number one, the AI-ready technology stack. Let's take a look under the hood. The data layer. I think you will all agree that there is no AI without data. In our industry, more so than in any other, data is all over the place. Public versus private, on-prem, on the edge, on the cloud, and pretty much everywhere. We work with mission-critical technical data like seismic, reservoir, and real-time operations data. They are stored on customer systems of record that are often proprietary, and many outside of the industry do not even know that they exist. Our customers do not want us to move or duplicate their data from their systems of record. In fact, they cannot, as data is core to their business processes, and any missteps that we make can cause serious issues. We have implemented a unique exploration and production data bridge from the ground up to honor all those customer constraints. Our data bridge is a fabric that allows us to connect to customer data sources without moving or replicating data. It is architected to work with the many, many data sources and cloud setups of our customers. It is what allows us to search, discover, access, and consume data in our AI workflows. The AI layer, it is arguably the most important. It is the magic dust on how SLB's AI differentiates. It just works for our industry. Everyone here is familiar with large language models and the weekly developments that we hear from frontier AI companies. We have seen many of our peers and our customers adopt and force-fit these models into their AI implementations. I can tell you this, that is an uphill battle to fight. Trying to decide which LLM to use, and worse, using these generic LLMs for technical workflows is really trying to boil the ocean. To uniquely solve this, we have built proprietary domain foundation models. Not one model, but models for several of our petrotechnical domains. These models are special in three ways. One, they don't replace those generic LLMs. They actually work in tandem with any customer preferred LLM. We solve for the domain specifics while these LLMs solve for the generic. Two, our domain foundation models are purpose-built. Purpose-built because we know exactly how domain data is structured, what to look for in that data, and how to use it to deliver on the user's intent. Three, because we know which parameters are important, we know what data to feed it. We have augmented our publicly available datasets with proprietary SLB data. We have absorbed the IP and knowledge that come from decades of oil field services into these models. What does it mean for our customers? It is simple. Our domain foundation models give them a powerful base model that is continuously updated. They can even refine these models within our platforms with their own data to customize them for their own assets. Three, the user experience layer. The key here is the Tela Canvas. Think of it as the ultimate industry Copilot. You all know how ingrained ChatGPT, Claude, Gemini have become in our day-to-day activities. Our users will soon find Tela indispensable because it is just as easy to use, and it is already integrated into the products that they use daily. Now, even more so because Tela understands their technical context, has strong guardrails that ensures that it never goes off-rails, and is built using domain benchmarks to ensure that it stays within the bounds of domain science. The second key element is our domain AI. Our AI implementations are structured to meet our customers wherever they are in their AI readiness. For organizations beginning their AI transition, we offer conversational experiences that extract insights from their data, from their project histories, and from their operational context. This is powered by an energy-specific LLM infrastructure that is trained on SLB's technical data, documentation, intellectual property, and essentially, our oil field experience. The barrier for adoption to our customers is very low, and the value for them is immediate. For those customers who are further along in their technical journey, our software embeds dedicated AI agents powered by our domain foundation models, skills, and tools. These provide high-value engineering recommendations while keeping the user in control of the decisions. For those customers that are advanced operators, our agentic framework runs fully autonomous workflows. They observe, plan, generate, act, and learn loop, but they are fully constrained at every step by domain science and physical guardrails. These agents are trained on validated domain data, they offer an assurance and accuracy that is unique to SLB. The third key element is our technology partnership. You heard from Trygve earlier about the breadth of our partner ecosystem. I want to go deeper into one in particular. Our partnership with NVIDIA is special. It is nearly a 20-year-old joint engineering program. We have direct access to their top engineers, and they choose to work with us for one specific reason. We bring the unique domain physics that is needed to push the boundaries of digital in energy. Together, we are building the Tela AI factory for energy to bring the most powerful set of agentic AI implementations in the industry to our customers. Let me be clear what this integration means. Guaranteed peak performance. Every domain foundation model we produce is optimized to be the absolute highest performing model in the industry. NVIDIA engineers are actively taking our source code and tuning it to run optimally for today's Blackwell chips, and they're already future-proofing it for tomorrow's Vera Rubin architecture. We are fusing the world's leading AI computing architecture directly with our unparalleled domain data and science. No one else can do this at scale today. It creates a competitive moat that simply cannot be replicated. We deliver these AI capabilities through two distinct user experiences, each one designed for a different mode of working. Tela Embedded integrates agentic AI directly in our existing widely deployed software, Petrel, Techlog, Trillo, OptiFlow, et cetera. Our users access conversational and agentic tools natively within these applications that they use every day. This drives immediate productivity gains and reinforces the value of our software for our users. This provides that indispensability that I talked about earlier. It is simply there for them to use. Tela Canvas is a standalone experience designed for broader cross-functional use. It works across application boundaries and data silos, orchestrating complex end-to-end technical workflows by combining AI with the physics-based domain science that forms the core of our software portfolio. Where Tela Embedded enhances individual application workflows, Tela Canvas connects them. Our customers can choose between rapid transaction-focused interactions via Tela Canvas or deep, immersive engineering workflows within our core applications. Both run on identical agentic AI backbone, the same domain foundation models, the same physical guardrails, and the same data infrastructure. Now let me show you what this looks like in practice, starting with planning. Our planning solutions and workflows are driven by an extensive portfolio of subsurface agents, models, and specialized tools that cover the full spectrum of technical workflows used in exploration and field development. They provide a very comprehensive coverage of the key domains across geophysics, petrophysics, geology, and reservoir engineering that Rakesh talked about earlier. Let's see an example of these planning agents in action within the Tela Canvas and connecting to Petrel, our leading subsurface platform. Log then. Tela immediately notifies them of new well data available for the southern part of Block C14. With a single click, they choose to view the data. The data is loaded into the IVAAP log canvas. Tela recognizes that this data has not been reviewed yet and offers to run a quality control check. The user agrees, and the well data is conditioned and QC'd automatically. With the data now ready, the user requests a porosity prediction for the reservoir interval. Using the domain foundation model, Tela predicts porosity and updates the canvas with a new log. The user asks for a list of seismic data in the area and guidance on which dataset is most suitable for structural interpretation and trap detection. Tela quickly provides a list of seismic cubes and highlights the BO Carry dataset as the best option for this task. With the dataset selected, the user asks Tela to identify a structural trap. Leveraging the domain foundation model, Tela detects a structural trap in the Vinton Dome area and displays the section. The structural trap is visualized, and Tela suggests performing a more detailed fault analysis. However, the user decides to handle the fault analysis manually and instead requests a search for fluid contacts within the trap. Using the anomaly detector agent, Tela identifies a pay zone and presents a 3D visualization of the area, providing critical insights for further evaluation. To refine the structural interpretation and prospect analysis, the user requests to load the new well and seismic data into Petrel. Tela seamlessly transfers all data, enabling the user to continue their work with ML-assisted seismic interpretation tools. In the Petrel application, the user has access to Tela in the side panel, and the conversation can continue. You just saw a glimpse of Tela in action, both as a Tela Canvas as well as Tela Embedded in Petrel. It shows how a combination of domain foundation models and other AI models integrated into a project workflow can completely transform them. I want you to think why this is so differentiating, why this demo could not have been done just six months ago. A typical exploration workflow to directly detect hydrocarbon-rich areas in the subsurface takes a team of geoscientists weeks to execute. We are transforming these complex nine steps into two simple clicks, almost magically. We are compressing weeks of complex analysis into a few hours, while covering a broader range of scenarios than was previously practical. Let me tell you how this works. You've heard me say domain foundation models several times. Let me explain what they are and the key role that they play in our AI implementations by using the seismic domain foundation model as an example. Seismic data is core to most exploration and field development workflows. However, seismic data modalities, its structure, and its format are very unique to our industry, and large language models are unable to work with them. What we did was we started with a base vision transformer model. We adapted it to handle those seismic data modalities. We incorporated seismic and geoscience domain priors and context, we trained it with public and SLB multi-client seismic datasets. The outcome is a rich and capable seismic foundation model with less than 1 billion parameters. For reference, leading frontier models are well beyond 1 trillion parameters today. The small parameter count means our models are cost-effective to develop and to operationalize. It will also allow our customers to then fine-tune these models with their data for their continued use in Delfi and Lumi platforms. As in planning, our operational execution relies on a dedicated, scalable portfolio of operational agents, models, and tools. These cover our drilling operations in our DrillOps family of products. They enable the increasing autonomy of complex operations, such as real-time geosteering that Cecilia talked about. On the production side, agentic workflows form the core of our Opti Suite of production offerings. These range from lift operations in wells to pipelines and networks to complex facility operations like FPSOs. Let me exemplify this from a deployment that we did for a customer in the Middle East. In traditional operating models, engineers must manually trigger, review, and process data to manage facility of equipment. This is an incredibly frustrating and monotonous activity for a production engineer, while for the company, this means operational adjustments can only be made when there is someone at the desk. What Tela does is that it converts these manual actions into autonomous evergreen loops, reserving human intervention only for high-value capital decisions. You might say, "So what?" When we talk about a production asset, we are talking about a lot of equipment. These come from different vendors, are of different vintages, each with different sensors, working with different parameters and data formats. All of them are being used differently in different conditions. Leveraging agentic AI is the only way to reach operational autonomy at scale while still retaining human oversight. We can do this. We can do this because our equipment digital twins are trained on real-world physics and are validated through continuous iterations. We can do this because we are OEM-agnostic and can support equipment from a wide range of providers. We can do this because we can model and simulate at the asset or system level. These enable round-the-clock facility optimization, directly lowering operating risks, minimizing unplanned downtime, and maximizing barrels produced. You will soon hear from Stéphane our broader monetization strategy, but let me be a bit bombastic for a moment. Every single agent, every model, every tool that a customer uses within our ecosystem, we have implemented the platform so that we can track their consumption every single time at scale. That tracking and provenance is exactly why and how we can monetize AI. We do this through four distinct channels. We already talked about Tela Embedded into our existing widely deployed software platforms. We monetize through upselling Tela subscriptions and then on the consumption of agentic workflows. Tela Canvas opens a new channel for monetization, where a base subscription paired with consumption-based pricing allows us to cross-sell to the existing customer base. It also creates new sales opportunities with those customers that find adopting platforms like Petrel to be a heavy lift. Going beyond these two channels, we also develop fit-for-purpose AI workflows for our customers through our innovation factory model, a network of seven AI centers of excellences around the world. These solutions are then deployed with the customer's Lumi and Delfi environments, creating long-term platform stickiness and ongoing consumption. Finally, the digital marketplace that we announced on Monday. It enables a platform business model for SLB and verified third-party developers to offer specialized agents, models, and applications that can be deployed in our digital ecosystem. We monetize through revenue sharing driven by consumption, a high margin, scalable channel that will grow with the ecosystem itself. As I conclude, I want to emphasize one critical truth. Today, no other company in our industry can do what SLB has accomplished. We did not ride the wave of generic AI models. We built proprietary domain foundation models from the ground up. We did not ask the industry to rewrite their operations. We embedded intelligence directly into the applications that tens of thousands of geoscientists and engineers trust every day. We have created an agentic framework that is open for our customers to extend and yet rigorous to operate autonomously within physical constraints. This combination of proprietary models, trusted platforms, deep domain science, augmented by strong digital partnership is what positions SLB to lead the commercialization of AI in our industry. It is a position that will allow us to be first and go further once again. Now, let me welcome Stéphane to the stage to discuss the financial impact of our digital business. Thank you. Good morning, everyone, and thank you for joining us today. Before we start, let me briefly step back and review the story you've heard so far. We have discussed the pivotal role of digital in our industry and the differentiated position SLB has built over time. You have seen how we are leveraging our platforms and applications across planning and operations workflows. You have heard about the opportunity to scale AI across our portfolio to unlock even greater value. What I would like to do now is bring that story together through a financial lens. Over the next few minutes, I will focus on three areas. First, the digital profile of our digital business. The financial profile of our digital business. Second, the significant market opportunity ahead of us and how we plan to monetize it. Finally, our 2030 financial ambitions. The key takeaway is this: digital has become a meaningful contributor to SLB's financial performance in the past few years, and we continue to see significant runway ahead with accretive growth and continued margin expansion. Let me begin with where the business stands today. In 2025, digital generated approximately $2.7 billion of revenue, more than $900 million of adjusted EBITDA, and an adjusted EBITDA margin of 35%. It also reached approximately $1 billion in annual recurring revenue on a trailing 12-month basis. What is most important is the quality of this growth. Since 2021, digital revenue has grown at a 16% compound annual growth rate, well above the oilfield services market and SLB's overall growth during the same period. Adjusted EBITDA grew even faster at a 23% CAGR compared with approximately 14% for SLB overall, demonstrating digital's strong operating leverage and differentiated earnings power. The margin profile you see here already reflects a meaningful share of the cost required to support growth as the research and engineering spend is directly expensed. That translates into very strong cash generation and effectively makes digital the division with the highest return on capital employed in the company. What digital brings to SLB is very clear. It adds growth, it lifts margins, and it delivers very attractive returns. Let me now describe our digital revenue footprint. One of the defining strengths of this business is that it is diversified across geographies, customer types and revenue categories. That matters because it gives us a broader opportunity set, greater resilience and multiple paths to growth. Today, our digital business serves more than 1,500 customers, including more than 90 of the world's top 100 oil and gas producers. That is a strong install base and a solid foundation for growth. Geographically, the business has broad exposure across the Middle East and Asia, Europe and Africa, Latin America and North America. Our customer mix is also well-balanced across national oil companies, independents and majors. That mix is important. With national oil company and independents, we already see strong digital adoption, particularly in planning workflows. With the majors, we see a meaningful runway. As some customers move away from internally developed systems towards scalable enterprise-grade platforms that can support broader digital transformation. Finally, from a revenue category perspective, platform as an application represents approximately 40% of digital revenue, followed by professional services, digital operations and digital exploration. That mix will evolve as digital operations continue to scale. We expect it to become the largest part of the business over time, as I will describe momentarily. Overall, this is a well-balanced business. It is not dependent on one geography, one customer or one product line. It is also supported by the breadth of the broader SLB portfolio and our global reach. Taken together, that gives us confidence in both the durability of the business and the opportunity ahead. Next, building on what Rakesh outlined earlier, let me turn to the market opportunity and where we see the strongest growth. Recent third-party analysis shows the total addressable market for our digital business growing to approximately $35 billion by 2030. That view aligns closely with SLB's internal analysis. When we map the market by category, we expect the strongest growth to come from digital operations, where the market is expected to grow at an 11% CAGR through 2030. This is compared with about 8% for the overall digital market. As I highlighted earlier this morning, there is meaningful upside to this outlook. If adoption of AI solution moves faster than currently forecasted, the digital market could expand to as much as $50 billion by 2030, representing a 15% CAGR. Together these trends, along with our differentiated market position, give us confidence that we can grow digital revenue at a 10%-15% CAGR through the end of the decade. With the higher end of this range based on accelerated AI adoption. This revenue trajectory would outpace both oil and gas upstream investment, as well as the industry's digital spend, as we believe we can leverage our digital platforms, customer footprints and AI capabilities to continue growing ahead of the market. Notably, we expect to deliver this level of revenue growth without significant M&A activity, although we will continue to consider bolt-on technology acquisition that can further strengthen our offering. With that as the backdrop, let me now turn to how we will monetize that opportunity. Our digital offerings are monetized through several commercial models, each contributing differently to growth, margins, and recurring revenue. Platforms and applications are largely recurring. They are sold through software subscriptions or perpetual licenses with annual maintenance. Digital operations has a different model. It is generally sold as an incremental digital line item connected to our core services or equipment. Revenue in this category is repeatable or sometimes recurring, and typically delivers high incremental margins. Digital exploration represents our exploration data business, which consists of a differentiated library of seismic surveys and other subsurface data covering key basins worldwide. This is usually highly profitable but non-recurring in nature, with revenue generated primarily through one-time license sales. Our success in producing and selling high-quality data is highly dependent on the use of our platforms and applications, enhanced by our domain foundation models. Finally, professional services is more project-based. It includes consulting and technology services required to support our clients' digital transformations. Although this category has lower relative profitability than the other digital categories, it remains strategically important because it helps drive adoption and creates pull-through across the broader portfolio. In short, we have multiple ways to monetize the digital opportunity. More importantly, these various models reinforce one another, and combined, they create a business with growth, resilience, and flexibility. Let me now go 1 level deeper into the 2 areas with the strongest growth potential, namely platforms and applications and digital operations, and explain how we will unlock further growth and value. In platforms and applications, we see 3 key levers for increasing monetization. First, gradually transitioning on-premises customers from perpetual licenses with maintenance to subscription models. This allows for better tiering of our commercial offering based on the features our customers choose to consume. Second, migrating more customers from on-premises offerings to the cloud. Third, monetizing consumption across the portfolio as customers expand usage of our platforms and applications, data environment, and AI solutions. As you can see, growth in platforms and applications is not only about adding customers. It is also about shifting the mix towards more recurring subscription and consumption or outcome-based models. This will improve revenue predictability, reduce sales volatility, increase contract lifetime value, and improve customer retention. The opportunity in digital operations is of a different nature and scale. Here, we believe we can increase the size of the market, if not create the market, by scaling connected equipment and autonomous workflows across customer operations with new AI capabilities further accelerating that trend. Today, those digital services only represent about 1.5% of our core equipment and services revenue, despite delivering significant results in the field. As customers increasingly recognize the benefits of these solutions, we see the potential for spending in this category to grow at an elevated rate, potentially tripling by 2030, supported by digital add-ons and increased outcome-based pricing. Taken together, the evolution of platforms and applications and digital operations are expected to drive a majority of the growth in our digital business. The value generated from these offerings will continue to compound. As platform usage increases, more data is organized and activated. As more assets and operations become connected, the opportunity to automate workflows expands. As AI becomes embedded in those workflows, the value we create for customer increases. All in all, this will support our ability to continue delivering attractive digital growth with margins that are highly accretive to SLB. To make this more explicit, let me now close by sharing our 2030 financial ambitions. Based on market growth and the trends we are seeing in terms of adoption and monetization, we expect to double digital annual recurring revenue to approximately $2 billion by 2030. This is supported by the assumption I shared earlier that digital revenue will grow at a 10%-15% CAGR from 2025 through 2030. We also see a path to approximately double our current adjusted EBITDA for digital to between $1.8 billion and $2 billion by 2030. With margins expanding to a range of 38%-42% towards the end of the decade. Our ability to achieve margins towards the higher end of this range will depend on our success in increasing the share of subscription-based revenue in our mix, the continued expansion of digital operations, and the addition of AI-driven capabilities that create incremental value for customers and support better monetization of the outcomes we help enable. In summary, digital is already helping to accelerate SLB's growth with accretive margins and compelling returns. As adoption continues to expand across platforms, operations, data, and AI, we see a clear path to sustained double-digit growth, continued margin expansion, and increasing contribution to SLB's overall returns over time. Thank you for your attention. I will now turn it back to Olivier. Thank you, Stéphane. Ladies and gentlemen, as we conclude, let me leave you with this. Digital is becoming central to how this industry plans, operates, and creates value. What you have heard today reflects a leading position SLB has built over many years. It is one that is powered by science, accelerated by AI, and built for the complexity of energy operations. We are the only company that brings together the domain expertise, the technology, the partnerships, and global execution to redefine what is possible where it matters most. This is just the beginning. In the age of artificial intelligence, new opportunities are being unlocked across all industries, and we are pursuing them not only through the digital frame we discussed today, but also through our data center solution business. There, we are extending our work with hyperscalers, the same partners we work with and collaborate in our digital upstream business to deliver the physical infrastructure required to scale AI. In that sense, SLB is uniquely positioned to benefit from the secular growth of AI in two ways: through the platform and digital solutions that transform energy operations and through the infrastructure that enables AI to scale. If there is one takeaway, it is this: Our digital leadership is real, it is differentiated, and it is creating long-term value for SLB and its shareholders. Thank you for joining us today and for your engagement throughout the session. With that, I would like to invite today's speakers to come with me on stage for the Q&A session. Thank you again for your attendance. It is now my pleasure to open it up to questions. If you have a question, please raise your hand and we will come to you with a microphone. Please introduce yourselves and ask only one question so that we can get to as many of you as possible. As you're thinking about your question, allow me to kick it off by asking Olivier about something we've been hearing a lot lately. Olivier, as we think about SLB's digital next phase, what gives you the confidence that this business can evolve into a scaled higher multiple engine, distinct from traditional oil field services, and what proof points should investors focus on today? Thank you, James. Indeed, I think I would state first thing is that we are not building our digital capability anymore. We have built it. We're here to scale it. If you look at the proof point of where we stand today, we are already going at double digit with expanding margins, and we are seeing a mix further evolving towards increased recurring and consumption-based revenue. What makes me confident is that we have a clear path forward. The clear path forward is resilient on digital operation and AI solution. The sandbox is a total SLB OFE footprint. That is unique. The capability we have together, the domain, the platform, including AI-ready stack, the partnership ecosystem we have developed, and the global reach, as we said, is unique. When you combine all of this, as we continue to scale, the ARR will shift upwards. The consumption base on our platform will start to be clear, and our margins will resemble software-like margins. When you put all this together, I believe this will deserve a higher multiple. I think it's no more physical growth. It is durable growth that will compound and create value for the company. Thank you, Olivier. Let's take questions now from the audience. We have one right up here up front. Hey, thank you. Marc Bianchi with TD Cowen. Thank you for the presentation. I'm curious to achieve these targets, I think you talked about $3 billion of R&D spend since 2016. Can you talk about what additional R&D spend is contemplated to get to these targets? Related to that, how do you see this initiative sort of helping the capital intensity of the overall business? Do we see a reduction in capital per dollar of revenue, for instance, as time goes on and you're able to implement more of these capabilities? Thank you, Marc, for the question. Stéphane, can I pass that one to you? Yes, of course. Thank you, Marc. Look, as Olivier mentioned, the foundations are built. We've spent actually decades and increased R&D in the last few years to get there. We are not going to stop there. We will always need to enrich the platform. In terms of R&D, you've seen the numbers over the last 10 years. I would expect this, of course, not to increase as fast as the revenue, if it ever increases. You will gain operating leverage from this, but we will continue to enhance the platform and invest into it. I have a question right here in the middle. Scott? Yes. Scott Gruber from Citigroup. Thanks for the presentation this morning. Super impressive. I'm curious about the pricing strategy for some of these services. Thinking back to the digital operations examples where autonomous drilling can save 25%-40% on the drilling time of a well. If you think about that in the context of a deep water well, it could be like $25 million. Which is a huge amount of savings. How do you guys think about what is the fair share of that savings for Schlumberger, SLB, sorry, I'm old school, for SLB to capture versus how much you share with the client? Obviously, you want to push the adoption of these services and scale it up, but there's a huge amount of value creation there. How do you think about the pricing strategy with that value creation potential? Rakesh, would you like to kick off that question and perhaps, Cecilia, on digital operations, you can have a follow-up? Thank you. I think for different categories of revenue, as we've reported, the pricing strategies, of course, vary. For the operations, as you rightly point out, significant value for our customers, and we will therefore be in a very strong position to be able to scale. In the operations, as I think Stéphane briefly mentioned, we are talking about almost very little new investment for us to be able to provide this value addition because of the fact that we are utilizing the existing hardware already, and we are just bringing new algorithms to be able to bring the value for our customers. Of course, we expect, therefore, the margins to be very, very significantly accretive, as I think mentioned by Stéphane. For the other categories, for example, in the platforms and applications, again, I think the fact that we have a very distinctive and a very strong offering, we expect to scale that. Therefore, the additional scaling would not cost us very much, which is why the confidence that we have in terms of even stronger margins in the years ahead. Then, of course, the agentic AI, that will bring significant value on top of what we are already charging, and that should bring significant margins for us going forward as well. If I look at those, each one of those categories has distinct advantages, which will continue to bring more margins for us going forward. Cecilia, perhaps you want to elaborate on operations? A couple of points other than what Rakesh has said. First of all, many and most of our contracts are performance-based contracts. When we get this additional digital add-on service, we actually increase revenue not just from digital, but also from our general operations. Second is many of our digital operations that we sell actually are agnostic. As in the completions example, when we merge the digital piece with our innovative hardware, that's when we see a step change in performance. It is also an enabler to bring additional pull-through revenue for the locations where we're not having operations there. Thank you, Cecilia. James. See you right here. Not James, yeah. Yeah. Sorry. James, question about the changing dynamics that we've seen, how it impacts the digital adoption in this space. Energy and power has changed a lot in the last 110 days. Of course, that change with energy security started in 2022 as well but has become more pronounced. Olivier, you're having a CEO to CEO conversation, and I'm curious what the feedback is from the customer base about the security of their operations as they move more and more information to the cloud and go more digital. Do they worry about cybersecurity? Do they worry about hacks, things like that? Does that limit, or have you created a platform where they're very comfortable that you can protect their data? Olivier, would you like to take the first part of the question, then perhaps we can pass it to Shashi for the second part? Yeah. The first thing I would say is, Canon, that what is happening today with energy security, the need for supply diversification, the need to secure and accelerate supply management is all playing to the strengths of the impact of digital in our industry. Anything I'm hearing from customers, the same way we heard back in 2020, is that digital is becoming more critical and more essential to unlock the performance efficiency to fast-track the cycle of first oil, first gas, and to improve recovery for the market, for the assets that can be deployed securely in the world. This is the trend that we see is only accelerating, is a secular trend that we believe that this crisis is only reinforcing. The role of digital going forward will be a shift and a critical transition for the industry. That is happening, and I think this is only accelerating. That's the feedback we're getting, and we are seeing it in adoption. We are seeing the pilots. If any mention of the impact, actually, our digital business in the Middle East has been extremely resilient against this backdrop of crisis. Let me add two points here. I think when we talk about customers and their concerns around their assets, I would put them into one aspect, which is around data. We implemented our digital platforms in a way that we can meet the customers where they are. For those customers that are comfortable with a traditional SaaS offering, great, we support all the three hyperscalers. There are customers for whom we have implemented what we call private SaaS, which means deployed solutions onto their tenant, which means it is managed by their own IT and security organization. That's one facet. Of course, there is a set of customers that want everything on-prem. We cover that entire spectrum to say wherever the customer is and their data are, we can deliver a solution there. The second angle I would say is from a cybersecurity point of view. We run one of the largest cybersec ops operations across the industry, and we work very closely with leading hyperscalers, plus also security companies like Palo Alto Networks, et cetera, on those, right? We are adopting and using the latest frontier models to test to validate our implementations or any kind of loopholes that might be existing. Then, of course, we work very hand in hand with the customer's own IT and security organizations as well. At the end of the day, for our customers to use our stack, they need to be comfortable that the implementations that we have meet their standards, and that's what we go with. Thank you, Shashi. Right here in second row in the middle. Dave, please. Thanks. David Anderson, Barclays. Stéphane, just a real quick point of clarification. On your 2030 targets, was that based on the $50 billion TAM or the $35 billion TAM? Dave, it's a range. This is why we have a range of EBITDA as well. The revenue itself is between 10%-15% CAGR through that period, right? The market overall, if you take the low end of the TAM we've given you, the $35 billion, that would be 8% CAGR. The $50 billion would be 15% CAGR. It's based on the entire range, if you want. Got it. Understood. Olivier, SLB has made a big point today about your mode in digital. You're really the only OFS company doing this. You've been doing this longer than anybody. The foundational models, the domain expertise gives you all a head start or a lead in AI. Your customers are also adopting AI. They're adopting agentic AI, all sorts of platforms as well. Where is that line today? Are you concerned about that line moving? In other words, your customers are going to be adopting some of this in-house. You're going to be providing other things, but is there a concern that that line could shift? What is the concern that some of them are going to be start adopting what you're doing? As you heard before, we meet our customer where they are in their digital journey. I think if you look back at the history of digital, 30 years ago, most of the reservoir simulators were owned and developed by our customers. Some of the basic interpretation was done the same way. Over time, the emergence of platform, industrial-grade platform, has replaced those developments. Nowadays, some customers are willing to enter the development of AI model, if not development of agentic AI, using models. What we offer is an open platform. We offer Delfi, Lumi, the data and AI open platform, and Tela as agentic agent framework that our customer can use to extend their agent team, connect to their agentic workflow, connect to their third-party applications, and also embed our domain foundation model or retrain our domain foundation model to their own data set. That's what is happening in a pilot we have with several customers, and they see a huge benefit of doing so because they have a starting base that is a step change from what they can do by themselves. As we said, the relationship with NVIDIA give us the guarantee that you have peak performance on the domain foundation model. We have designed it from the ground up, not using the existing Frontier model. We are designing using our science, our technology from the ground up with the guardrails that you integrate it from NVIDIA, from other provider into it. The starting point is very strong. The framework we have give them the freedom to extend, and that's what is attractive into our offering to the customer today. Yes. Right back here. Right here in the middle. Can someone pass the microphone? Yeah. Hi there. Sebastian Erskine from Rothschild & Co. Just a question. In one of the presentations, you mentioned about the performance-based contract in Libya, actually trying to buy in a bit to the efficiencies that customers can gain. Obviously, that's interesting to me. When we look at U.S. land, one of the big stories was the deflation services, the fact that E&Ps could do more with less. How much as a % of these performance-based contracts or pricing-based, outcome-based models do you see and a scope for that in digital operations going forward? Thank you. Cecilia, I think you answered part of that question earlier. Yeah. It's a large % of our contracts are performance-based contracts. I believe you were asking specifically on the U.S. market. In U.S. market, we have a very flexible go-to-market approach. We rent and sell our equipment as well as do the services. Many of our services are performance-based, then the rental and the sale of our equipment is through a third-party competitor. Yes. Right back here. Thanks. Heath Terry, Citi. Really appreciate you taking the time on all of this, particularly the level of detail around some of your technology partnerships. The reliance that you have on the cloud providers, they've obviously been very vocal about the issues that they're dealing with from a supply perspective and the constraints with demand increasing the way that it is. That's showing up in pricing. It's showing up in this whole issue around token costs going up as we've started referring to as token maxing. I'm curious if you're seeing any of those kind of issues showing up in your relationships, either with the hyperscalers or with your customers as those underlying costs start to go up and how you're planning longer term against the constraints that seem like they're going to be around for a while in this space. Trygve, you explained to the audience the digital advantage and the partnership model. Why don't we pass this question to you? Yeah. As you say, we have a close relationship with all the hyperscalers, all the major cloud providers. We, of course, secure ourselves for our own direct expenses. We secure ourselves with long-term contracts with these providers to ensure that we have cost-competitive access to the technologies. We also work very actively with them, particularly on securing capacity, where we have a well-established playbook for securing that we have the right capacity. As our workloads will be sometimes demanding the same type of capacity they use for other workloads, so make sure that we can continue providing continuity to our customers in operating. Rakesh, would you like to elaborate further? Heath, actually, you do make a good point. There is clearly a transition happening, and the industry is getting used to the changes that are happening. I'll say there is a very interesting trend that is happening right now. Instead of going from cloud first, many of our customers are going to what they call hybrid cloud for elasticity. They want to keep on-prem for consistency, and then they go on the edge for immediacy. They are moving in a direction where they will actually have infrastructure which encompasses all of them, so that they're able to take the benefit of what the cloud compute brings as well. They are also prepared so that they are able to get the maximum benefit from what they have in-house already, and also from the edge operations where it is required. Thank you, Rakesh. Olivier? What is important to this is that to offer our customers the ability to navigate through this tenant hybrid cloud for elasticity of cloud compute and edge at the same time, doesn't come in a quarter. It has taken us years of deployment, of tuning, of testing and validation, and certification for customer. Proud ourselves to be the only one that can do this complex environment at scale, industry grade, complex architecture that combine the benefits that you heard about, that allow our customers to use the cloud when and as necessary, and remain in that tenant where they believe it is more secure and they have the capacity they can to develop their workflows. That's unique. Thank you. In the very back, I see a hand up. Hi. Thanks. Stephen Gengaro, Stifel. When we think about digital and we think about maybe the last few years and then now through 2030, how do you think that impacts your growth versus history in the core business? Stéphane, let me go ahead and pass this one to you. Did you hear the question? Yeah. Actually, if you don't mind rephrasing. Yeah, very good. Stéphane? maybe relative, unless you want to tell us what you think the market does for the next 5 years, but relative to the market through 2030, how do you think digital impacts the growth in your core operations versus the peer group? Okay, got it. Sorry for that. Look, first, the growth we are portraying here for digital, and we've said this before, we believe is at least partially de-correlated from the growth of our core services and equipment, which as you know, are more cyclical. If we are confident to give that 10%-15% CAGR there for digital only, is that we think this is really secular, structural, and triggered more recently by the acceleration of AI. That gives us confidence that there is this pot of digital, if you want, that can grow a bit regardless of what can happen in the rest of the E&P upstream sector. Particularly because it remains a very small % of the total spend, as you've seen. Now, can that influence the size of the overall E&P spend? Yes, it can. What it can do, at least for us, is that it can bring more, first more digital. Because, as Cecilia highlighted, it's not just about the software and the platforms, but it is the connection with the hardware, is that more digital is going to pull through more core services as well. We want them to gain in efficiencies and generate cost savings. This is not going to happen in the core services and equipment we provide. To the contrary, we are going to have a boost from the advent of more digital operations. Thank you, Stéphane. Yes, Doug. We'll get you a microphone right here. Thank you. Doug Becker with Capital One. Curious about, as autonomous operations really start to scale, how are you thinking about risk management? What safeguards are in place from a suboptimal decision made by an autonomous operation or maybe in an extreme example, a well control incident that was really triggered by an autonomous decision? Thank you, Doug. We're going to pass that one to Cecilia. Just like a self-driving car like Tesla, the system can go into manual mode at any time, and the user can decide whether to go autonomous or if the recommendation needs to be approved by the user. It's a very easy on/off, and ultimately, there's always going to be a user that makes the final call, which is going to be our customer. Thank you, Cecilia. Saurabh, did you have your hand up? Yeah, right up here in the front, please. Hi, Saurabh Pant, Bank of America. One thing, Olivier, when you took over as the CEO back in 2019, you were talking about the fit-for-basin at that point of time. I think I heard the word fit-for-basin once in Shashi's remarks. How do you think about fit-for-basin from a digital perspective? I know you talked about seven, I think, innovation factories across the globe. Maybe talk to how are you thinking about that? What are you doing differently in different parts of the world? Olivier, why don't you go ahead. Yeah. Great question. I think if digital brings us one thing, is ability to customize, to tailor, and to fit our digital frame to the basin challenge that we are facing. I think the concept we have put together with the industrial factory, and we have seven of them in the world, were to provide the digital backbone, the digital domain expert, the digital platform, close to our customer to collaborate on what could be done locally to make fit technology, digital technology solution. Now, with the advent of digital operation, the advent of agentic AI, we are going to the next level. The next level of putting together, stitching together OFE operation with digital capability and creating unique set of fit operation with a fit domain foundation model, with fit set of workflows that are stitched together through an agentic AI, and with a fit set of equipment or services provided back to back. The best example actually happening today that we can refer to, it's what you heard about at ADNOC, referring to it as AI PSO. An AI PSO is production optimization using AI. We are co-developing the agents. We are fitting this agent to work on the specific asset of ADNOC, and we are lifting and enhancing the production performance through this. It's a fit application of AI capability tailored to the OEM equipment that they use, tailored to the reservoir characteristics that they have, using our Delfi and our Lumi platform to make it work together. That's the principle, that's what we want to extend. That's what we want to repeat from basin to basin. Trygve, did you wish to add any additional color? Just there's one more color to fit for basin as well that is increasingly being important now and which is underpinned by our platform investment over the last few years, and that is the technology sovereignty. A lot of operators around the world are increasingly concerned about their sovereignty, their ability to operate their digital environments. This is exactly what our platform has been built for and enabled for the last few years, and I would say we are uniquely positioned to be able to guarantee our customers this type of sovereignty as well. That's the additional thing in addition to the particular operational and geological challenges they have as well. Cecilia. I want to add a different angle to the question. Every geography is going to be different, and the system needs to learn what are the parameters for that geography. For example, a deep water operation is directional drilling is going to look completely different than U.S. land. What the customer wants is going to be completely different. In deep water, it's about landing the operation per the plan in the sweet spot with a minimal amount of risk. In the U.S., it's about drilling as fast as possible. As long as you're in the tunnel, you're fine. The system learns and gets smarter depending on which geography and what type of operations you're running, hence why it's very important to have this wide footprint that we have at SLB. In the very back. Yeah, please keep your hand raised. Thank you. Ati Modak from Goldman Sachs. I wanted to connect a few dots. I think Shashi, you mentioned generic LLMs are challenging to do. Olivier, you mentioned at the beginning that it's important to know what to build. We've been hearing customers trying to build their own applications. Where are we in that evolution of that dynamic? I'm curious how that evolution is factored into or affects the sensitivity on your 2030 guidance. Shashi, would you like to take the first part of the question? Yeah. I think, we talked about LLMs because they are very powerful tools, but they're very statistical in nature. They build and they generate the next response based on the context you provide. We cannot take that risk when we are talking about technical workflows where customers are making high-value decisions or high-risk decisions, right? What we want to do is to say we will leverage the large language models where they bring value, which is converting the context into an outcome. When the context is set by us, by providing the domain. That means when we are working with a well log foundation model or a seismic foundation model, that absorbs the knowledge that comes from that domain and does the handoff between the foundation model and the large language model to aggregate the information and serve it out, right? That way, we don't ask the large language model to figure out how to work with seismic data. It has no clue, but we do. We work with that balance of us providing the domain context and informing everything based on the domain, and use the large language model for where it is best suited, which is to aggregate and summarize and provide the outcome to the user. I'll pass it to Rakesh. Yeah. I think, I want to also bring in Dave's point that I think you were alluding to. Many of our customers have actually tried, absolutely they will continue to try to go down that alley as well. They're realizing more and more that the changes are happening at such a rapid pace that unless you really have the expertise and you're engaged in it on a regular basis, this is not a pace that you will be able to keep up with. More and more, we are seeing that the customers are actually aligning with partners that they realize are going to be in this for the long game. The other comment I want to make, we're talking about LLMs a little bit. LLMs are based only on text. The data that we have in our industry is in very other different formats. seismic formats have nothing to do with text. Logs are completely different, and therefore the models, the domain foundation models, naturally, the LLMs cannot do anything with the data that we have in our industry. The domain foundation models have a very distinct application that will continue to bring value to our industry specifically, and only companies who can handle that kind of data will be able to benefit from it as well. I just wanted to give you those two colors. Thank you for that, Rakesh. Right here. Dan? Hey, thanks. Good morning. I just wanted to ask a question on labor and kind of talent retention. The catalyst for the question was, I noticed in one of the earlier partner testimonials, it was someone who had actually been at SLB for a couple of decades, and then most recently was at one of your biggest competitors. Yeah. Can you just talk about to what extent attracting talent, retaining talent is a bottleneck or any type of impediment to growth for SLB? Also, if it's something when you speak with your customers, if training and attracting the right talent is a bottleneck for their digital adoption as well? Thanks. Olivier, why don't you? I think we all compete for the same talent pool. I think we have demonstrated for the last decade that I think we have still the foundation, the culture, the training framework to attract talent, digital talent, geoscience talent, people, technical experts, engineer talent that we train. We co-train in AI and in data science as well as in geoscience domain. We have been able to attract from every region, top talents across the best university. Occasionally, we compete with those hyperscalers. We compete with some other horizontal player. I think the talent we have in our team has allowed us to build what you have seen today, to build the Tela infrastructure, to build the Delfi, to build the Lumi. I think it speaks volume to the talent we have that Shashi is leading and our team is leading. I'm very proud of what we have as a talent pool in our team. I'm convinced we'll continue to attract, I think, these events and what we are publishing every day and the path to autonomy is what is exciting the most new and future employees and prospects that are joining us. They love what they can see when they enter the company. They see that we are becoming a digital-first company, and I think that is very attractive, and I think that is the magnet we are putting for digital talent throughout the next few years. I'm not concerned. I'm excited about the future can give us with this talent pool we are attracting. Thank you, Olivier. Hey, Keith Beckmann from Pickering Energy Partners. It sounded like M&A is probably not a key way to grow. You guys got a lot of internal things going on. On that front, is there anything within the digital portfolio that you think you're missing? Maybe what are some of the key characteristics you're looking for when evaluating potential opportunities? Thank you, Keith, for your question. I'll pass that to Rakesh. Keith, clearly, we are always on the lookout for bolt-on technologies that will bring value. We've announced a couple, I think, over the last few months that I'm sure you are aware of. I'm not going to sit here and tell you this is the weakness we have in our system. We are always on the lookout for technologies which will complement what we have or for bolt-ons that we decide we will not develop in that particular domain or that particular part of the technology. I think both extending our partnerships with companies that have complementary skills that we will either integrate or we've decided not to compete. Occasionally, where we see that is a good fit into our own organization as we have done, we will continue to look out for opportunities. Thank you, Rakesh. I think Destiny Global and Tigo's are good examples of that. Derek. Right here first. Thank you. Derek Podhaizer, Piper Sandler. I found it interesting when you split apart the customer type for digital. I think you had 37% NOC, 37% independents, 21% for the majors. Maybe could you talk about the opportunities to capture more share with the majors or on the flip side, some of the limitations and headwinds to continue to drive adoption in with the majors? Go ahead. I think you have seen three statements from Eni, from Chevron, from TotalEnergies, and from Shell. I forgot about Shell in this statement. They're very, very clear of the benefit they've seen partnering with us. They all collaborate with us on a different scope, utilizing digital operation, trying to get the most of autonomy for drilling operations. Chevron is the historical partner that has helped us develop and accelerate our platform at scale with Microsoft. Both Shell and TotalEnergies have entered a collaboration agreement with us to develop fit subsurface and adapt their workflows to the benefits of the organization. I don't see any limitation on this. I see organization on the customer side that are keen and eager to leverage and to work side by side with us so that they can leverage agentic AI environment. They can leverage the powerful platform so that they can deploy to the complex environment they will always want to deploy to match security requirements they have, sovereignty when operate in certain country, and leverage of their own IP, which our platform allows us to plug in. I don't see a cycle. I see a big runway with all the major and the ones that were mentioned into this to continue to work with them for adoption at scale. Very good. Right here. Thanks. Phillip Jungwirth with BMO. Can you talk about the drivers behind the margin improvement by 2030, 38%-42% is quite a bit higher than 35% in 2025, and I think you guided a similar level here in 2026, despite the 9% growth. Is it mainly just mix shift with platforms and applications, digital operations growing more, or is there more behind it? If so, could you please expand upon that? Thanks. Very good. Stéphane, I'm going to pass this one right to you. Look, first, I'm quite confident we can reach that range towards the end of the decade, if not earlier. I think actually margins will increase year after year into 2030 to reach these levels. The key driver is a few things. First, you have the simple operating leverage. We've mentioned R&D before. R&D, if you want, is the biggest cost to grow. Again, the heavy lifting is done, and if we increase R&D a little bit, it's not going to increase for sure as much as the revenue growth. You get margin expansion from there, you have that shift in pricing model. Some of it is enabled by AI. We believe we will be able to increase the subscription-based revenue, which allows us to tier better, if you want, the levels of pricing, depending on the features each customer use. More consumption-based, more outcome-based pricing should help us lift the margins as well. It's the combination of all this that really gives us the confidence that 38%-42%, the midpoint of 40%, if you want, is quite a good ambition I think we can reach. Thank you for that perspective. Allow me to come back to this side of the audience. Yes, right here. Hi. Noah Naparstek from Goldman Sachs. I have another question on the mix. If we look at the 60% or so of revenues that's recurring and repeating, just wondering how weighted it is to pure SaaS. Do you plan to increase SaaS mix over time? How do you plan to do that? Yes. I'll pass it back to Stéphane. Yeah. Definitely we do, yes. It's part of the driver is indeed the SaaS mix. Again, we are not betting everything on the cloud, right? Because as we mentioned before, we leave the customers where they are. Still, we are seeing that shift. Is it going as fast as we want it to be? Maybe not, but it is going. Today, we have, if you want, a bit less than 50% on the cloud, and we could very much go to around 75% at one stage of SaaS and cloud. It's part of it. Olivier. The other element is the consumption model as part of the science. I think the use of AI, the use of agent, as you have seen a demo, as was shown by Shashi earlier today, you can imagine the compounding effect of deploying agents that can then run autonomously part of our engines that are either on the cloud or on the tenants, and consumption is based on the frequency and intensity of use of this application. That's this compounding effect that we believe will drive the way forward. Do we have any further questions from the audience? Yes. Right here. Thank you. Keith Mackey with RBC. The digital operations TAM expansion is certainly key to the growth metrics here. Can you just talk about what some of the key customer impediments to adopting digital operations has been, and how do you mitigate that to drive the further adoption going forward? Thank you, Keith, for the question. Cecilia? Sure. Thanks for the question. Excellent question, in fact. What we see is that customers like to pilot and test the system first to really understand the value it brings and to ensure that it's a safe operations and it fits everything that they would like to see out of the tool. Just to give you an idea, the last 6 months, we've done as much autonomous feats drilled than the first 2 and a half years. It's taken us quite some time to get those pilots, to get our customers to feel comfortable with it. Now we're starting to see quite a lot of uptake and an acceleration of uptake. The second thing is that a lot of customers are waiting to see who's going to go first. Now we have enough pilots that we're actually seeing customers almost not wanting to be left behind, and they're starting to be very interested in what we have to offer. We have time for one final question. Yes. Right there. Thank you. Heath Terry again from Citi. You obviously have operated for a very long time in some of the most geopolitically sensitive parts of the world. This past weekend, we got a bit of a wake-up call with the U.S. government's decision to effectively ban access to one of the large language models. How does that potentially impact the way that you and your customers are operating around this? Does it lead you to want to use more open source? Does it lead you to want to have more distributed systems in terms of where your own technology or where your customer technology is sitting? Thank you for that final question. Shashi, why don't you go ahead and take the question, and then we'll leave it to Olivier for closing remarks. Yeah. It's a very good question. I think when we started this journey, the LLM providers was few and select, but now the level of capabilities that we will need from an LLM to integrate into our technical solutions is getting to a point that you can get it from a large number of providers. What we have done is that while we leave this choice of a specific LLM to a customer because they may have an internal enterprise-level choice, we also make sure that we implement our technology stack from the point of view of supporting open models. We partner with NVIDIA, we have NVIDIA's Nemotron models as the models that we can deploy ourselves. We don't have to wait for a CSP to provide it in a particular area. It can be deployed on-prem or within a customer's environment. Similarly, we have models from Mistral. We have several options. We keep that options open. Even our own domain foundation models start from a base model that is open source, so that we are not tied down to a particular provider and get our hands in a bind at some point in time. It matters to our customer. They realize when they are walking with us through and discover the way we have built this model, the way we have factored open source or open protocol into our Tela framework, into our Lumi, into our GenAI, reinforce the attractiveness and the confidence they can bet on this technology platform for the future. Just to conclude, I think we had run through for the last more than two hours. I hope we convince you that I think we have a unique moat as a digital leader in our industry. We are building it on four clearly distinct combined capabilities, deep domain expertise that is rooted 100 years ago, a platform approach that includes an AI-ready stack, an ecosystem with partners that you have heard about that is unique and are willing to, and making every effort to work with us. Finally, ability to scale. Not only to scale AI, but to scale in digital operation and to scale and use the footprint and sandbox of our oilfield services and equipment potential. To reach all of our customers and to then help transform this industry to be digital first. That's the way we are willing to lead the future, to be recognized as digital-first company that help transform and unlock new level of efficiency, performance, and value for this industry. We believe we are there to lead this, to create this shift that industry needs for energy security, for energy affordability, and for the future of growth in our societies. That's where we believe we have a role to play, and that's what we wanted to share with you today. Again, thank you for joining us. I hope that you got enough information to help you model the future and recognize what you believe will be an elevated multiple for the company going forward. Thank you very much. Thank you, everyone. That completes the formal portion of our program today. On behalf of the entire team, we thank you for your time, your thoughtful questions, and your continued engagement. We hope today's session clearly demonstrated not just the current strength of our digital business, but the distinct competitive advantages that will drive our next phase of growth. We are incredibly excited about the opportunities ahead and our ability to deliver long-term value for our shareholders. With that, we will conclude today's livestream.

Speaker 8: Good morning, thank you for joining us for SLB's Digital Investor Day. I'm James McDonald, Senior Vice President of Investor Relations and Industry Affairs. This is an exciting time for our industry. Digital is reshaping the way energy is planned, produced, and optimized, and AI is accelerating that shift. At SLB, we operate at the intersection of energy and AI, and as digital scales across the energy value chain, it creates new opportunities for our customers and SLB. Over the course of the morning, you will hear from several of our leaders who will take you through our digital journey, our portfolio, and our strategy, and how this business will continue to support our long-term growth endeavors. We will conclude with a Q&A session, then we will host a lunch, where you will have the opportunity to engage directly with our leadership team. Good morning, thank you for joining us for SLB's Digital Investor Day. good morning thank you for joining us for slb's digital investor day I'm James McDonald, Senior Vice President of Investor Relations and Industry Affairs. i'm james mcdonald senior vice president of investor relations and industry affairs This is an exciting time for our industry. this is an exciting time for our industry Digital is reshaping the way energy is planned, produced, and optimized, and AI is accelerating that shift. digital is reshaping the way energy is planned produced and optimized and ai is accelerating that shift At SLB, we operate at the intersection of energy and AI, and as digital scales across the energy value chain, it creates new opportunities for our customers and SLB. at slb we operate at the intersection of energy and ai and as digital scales across the energy value chain it creates new opportunities for our customers and slb Over the course of the morning, you will hear from several of our leaders who will take you through our digital journey, our portfolio, and our strategy, and how this business will continue to support our long-term growth endeavors. over the course of the morning you will hear from several of our leaders who will take you through our digital journey our portfolio and our strategy and how this business will continue to support our long-term growth endeavors We will conclude with a Q&A session, then we will host a lunch, where you will have the opportunity to engage directly with our leadership team. we will conclude with a q&a session then we will host a lunch where you will have the opportunity to engage directly with our leadership team Before we begin, I'd like to remind you that today's remarks will include forward-looking statements. These statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied. The presentations will also include certain non-GAAP financial measures. Please refer to our SEC filings and the materials posted on our investor relations website for additional information. Please note that in the event of an emergency here today, NYSE personnel will be on hand to direct you to the nearest exit and provide further instructions. Let's begin the show. Before we begin, I'd like to remind you that today's remarks will include forward-looking statements. before we begin i'd like to remind you that today's remarks will include forward-looking statements These statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied. these statements are subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied The presentations will also include certain non-GAAP financial measures. the presentations will also include certain non-gaap financial measures Please refer to our SEC filings and the materials posted on our investor relations website for additional information. please refer to our sec filings and the materials posted on our investor relations website for additional information Please note that in the event of an emergency here today, NYSE personnel will be on hand to direct you to the nearest exit and provide further instructions. please note that in the event of an emergency here today nyse personnel will be on hand to direct you to the nearest exit and provide further instructions Let's begin the show. let's begin the show

Speaker 32: What does it take to shift an industry? It takes vision, it takes capability, it takes the courage to be first. SLB has been shaping the digital backbone of our industry for decades, we've had a lot of firsts. The first to simulate and predict reservoir performance. The first service company to build a global computing network. The first to create software with an open architecture. The first to move upstream platforms to the cloud. The first to drill and steer a well autonomously. The first to deploy agentic AI for upstream operations. Being first is one thing. Going further is another. Going further means building data-driven platforms designed for scale, with insights collected, curated, and connected across operations. Where agents become teammates. Combining domain expertise with digital intelligence. What does it take to shift an industry? what does it take to shift an industry It takes vision, it takes capability, it takes the courage to be first. it takes vision it takes capability it takes the courage to be first SLB has been shaping the digital backbone of our industry for decades, we've had a lot of firsts. slb has been shaping the digital backbone of our industry for decades we've had a lot of firsts The first to simulate and predict reservoir performance. the first to simulate and predict reservoir performance The first service company to build a global computing network. the first service company to build a global computing network The first to create software with an open architecture. the first to create software with an open architecture The first to move upstream platforms to the cloud. the first to move upstream platforms to the cloud The first to drill and steer a well autonomously. the first to drill and steer a well autonomously The first to deploy agentic AI for upstream operations. the first to deploy agentic ai for upstream operations Being first is one thing. being first is one thing Going further is another. going further is another Going further means building data-driven platforms designed for scale, with insights collected, curated, and connected across operations. going further means building data-driven platforms designed for scale with insights collected curated and connected across operations Where agents become teammates. where agents become teammates Combining domain expertise with digital intelligence. combining domain expertise with digital intelligence Where equipment is connected, intelligent, and autonomous, where decisions are made with confidence for every well, every barrel, every customer. This is the future we are building, not just as a vision, but as a reality delivered at scale. A future where intelligence is embedded everywhere energy is. Where technology doesn't just optimize performance, it delivers impact. This is how we go further. This is how we lead. This is the next chapter of SLB. Where equipment is connected, intelligent, and autonomous, where decisions are made with confidence for every well, every barrel, every customer. where equipment is connected intelligent and autonomous where decisions are made with confidence for every well every barrel every customer This is the future we are building, not just as a vision, but as a reality delivered at scale. this is the future we are building not just as a vision but as a reality delivered at scale A future where intelligence is embedded everywhere energy is. a future where intelligence is embedded everywhere energy is Where technology doesn't just optimize performance, it delivers impact. where technology doesn't just optimize performance it delivers impact This is how we go further. this is how we go further This is how we lead. this is how we lead This is the next chapter of SLB. this is the next chapter of slb

Speaker 13: Ladies and gentlemen, good morning, and thank you for joining us today. As you have seen, progress in our industry belongs out to those willing to be first, to go further, and to turn vision into reality. That same spirit of innovation is what brings us here today. This morning, we discuss a force that is reshaping how energy is discovered, developed, and produced. That force is digital. For many years, our industry viewed digital as an enabler, a bolt-on tool to improve workflows and to create pockets of value. Today, that has changed. Digital has become foundational. It unlocks performance, efficiency, and returns across every aspect of energy operations. For SLB, it is redefining how we grow, how we differentiate, how we create value. This is not a cycle. It is a structural shift in how this industry will operate. SLB is positioned to lead it. Ladies and gentlemen, good morning, and thank you for joining us today. ladies and gentlemen good morning and thank you for joining us today As you have seen, progress in our industry belongs out to those willing to be first, to go further, and to turn vision into reality. as you have seen progress in our industry belongs out to those willing to be first to go further and to turn vision into reality That same spirit of innovation is what brings us here today. that same spirit of innovation is what brings us here today This morning, we discuss a force that is reshaping how energy is discovered, developed, and produced. this morning we discuss a force that is reshaping how energy is discovered developed and produced That force is digital. that force is digital For many years, our industry viewed digital as an enabler, a bolt-on tool to improve workflows and to create pockets of value. for many years our industry viewed digital as an enabler a bolt-on tool to improve workflows and to create pockets of value Today, that has changed. today that has changed Digital has become foundational. digital has become foundational It unlocks performance, efficiency, and returns across every aspect of energy operations. it unlocks performance efficiency and returns across every aspect of energy operations For SLB, it is redefining how we grow, how we differentiate, how we create value. for slb it is redefining how we grow how we differentiate how we create value This is not a cycle. this is not a cycle It is a structural shift in how this industry will operate. it is a structural shift in how this industry will operate SLB is positioned to lead it. slb is positioned to lead it To understand the opportunities ahead, let's begin by discussing the challenge we must address. Energy is the foundation of modern life. Without it, societies cannot prosper, economies cannot grow, and progress cannot be sustained. Yet, as the world enters a new phase of demand, the role of energy is becoming even more important. From advanced manufacturing to cloud computing, transportation networks to AI models, urban growth to national resilience, the modern economy is becoming more energy-intensive. At the same time, expectation around energy are rising. Not only does the world need more energy, it also demands reliability, affordability, and sustainability. To meet this, our industry must achieve new levels of performance and efficiency. This is where digital changes the equation. Digital enables us to produce more intelligently, improving decision-making, automating workflows, and increasing recovery. While energy transformed the world, digital transforms energy. To understand the opportunities ahead, let's begin by discussing the challenge we must address. to understand the opportunities ahead let's begin by discussing the challenge we must address Energy is the foundation of modern life. energy is the foundation of modern life Without it, societies cannot prosper, economies cannot grow, and progress cannot be sustained. without it societies cannot prosper economies cannot grow and progress cannot be sustained Yet, as the world enters a new phase of demand, the role of energy is becoming even more important. yet as the world enters a new phase of demand the role of energy is becoming even more important From advanced manufacturing to cloud computing, transportation networks to AI models, urban growth to national resilience, the modern economy is becoming more energy-intensive. from advanced manufacturing to cloud computing transportation networks to ai models urban growth to national resilience the modern economy is becoming more energy-intensive At the same time, expectation around energy are rising. at the same time expectation around energy are rising Not only does the world need more energy, it also demands reliability, affordability, and sustainability. not only does the world need more energy it also demands reliability affordability and sustainability To meet this, our industry must achieve new levels of performance and efficiency. to meet this our industry must achieve new levels of performance and efficiency This is where digital changes the equation. this is where digital changes the equation Digital enables us to produce more intelligently, improving decision-making, automating workflows, and increasing recovery. digital enables us to produce more intelligently improving decision-making automating workflows and increasing recovery While energy transformed the world, digital transforms energy. while energy transformed the world digital transforms energy This is the next chapter of value creation in our industry. This is why we have positioned SLB at the forefront. Unlocking the full potential of digital energy requires domain expertise, global scale, trusted relationships, and a digital platform foundation that connects the full life cycle of energy operation. SLB is bringing this capability together in a way few others can. At the moment when the industry needs them most. Today, we're navigating a complex environment, one where energy security has become more critical. Assets are becoming more mature. Customer remains disciplined in how they allocate capital. Against this backdrop, four structural priorities are driving investment across this industry. Improving operational performance, increasing recovery, reducing cycle time, and delivering greater capital efficiency. These priorities are durable, they are investable, and they increasingly favor digital. First is operational performance. This is the next chapter of value creation in our industry. this is the next chapter of value creation in our industry This is why we have positioned SLB at the forefront. this is why we have positioned slb at the forefront Unlocking the full potential of digital energy requires domain expertise, global scale, trusted relationships, and a digital platform foundation that connects the full life cycle of energy operation. unlocking the full potential of digital energy requires domain expertise global scale trusted relationships and a digital platform foundation that connects the full life cycle of energy operation SLB is bringing this capability together in a way few others can. slb is bringing this capability together in a way few others can At the moment when the industry needs them most. at the moment when the industry needs them most Today, we're navigating a complex environment, one where energy security has become more critical. today we're navigating a complex environment one where energy security has become more critical Assets are becoming more mature. assets are becoming more mature Customer remains disciplined in how they allocate capital. customer remains disciplined in how they allocate capital Against this backdrop, four structural priorities are driving investment across this industry. against this backdrop four structural priorities are driving investment across this industry Improving operational performance, increasing recovery, reducing cycle time, and delivering greater capital efficiency. improving operational performance increasing recovery reducing cycle time and delivering greater capital efficiency These priorities are durable, they are investable, and they increasingly favor digital. these priorities are durable they are investable and they increasingly favor digital First is operational performance. first is operational performance Customers need to perform with greater speed, consistency, and precision across increasingly complex operations. That means reducing non-productive time, improving reliability, and using technology to deliver better outcomes. In this environment, operational performance is no longer just a measure of execution. It is a source of competitive advantage. Second is increasing recovery. As the resource base is becoming more mature and complex, more of the next source of value creation will come from existing assets themselves. Customer needs to understand reservoir more deeply, manage production more dynamically, and apply technology that improve recovery over time. It is no longer enough to bring production online. The greater value lies in maximizing recovery throughout the life cycle of an asset. Third is cycle time reduction. Customer needs to move faster from planning to production. From discovery to first oil and gas. Customers need to perform with greater speed, consistency, and precision across increasingly complex operations. customers need to perform with greater speed consistency and precision across increasingly complex operations That means reducing non-productive time, improving reliability, and using technology to deliver better outcomes. that means reducing non-productive time improving reliability and using technology to deliver better outcomes In this environment, operational performance is no longer just a measure of execution. in this environment operational performance is no longer just a measure of execution It is a source of competitive advantage. it is a source of competitive advantage Second is increasing recovery. second is increasing recovery As the resource base is becoming more mature and complex, more of the next source of value creation will come from existing assets themselves. as the resource base is becoming more mature and complex more of the next source of value creation will come from existing assets themselves Customer needs to understand reservoir more deeply, manage production more dynamically, and apply technology that improve recovery over time. customer needs to understand reservoir more deeply manage production more dynamically and apply technology that improve recovery over time It is no longer enough to bring production online. it is no longer enough to bring production online The greater value lies in maximizing recovery throughout the life cycle of an asset. the greater value lies in maximizing recovery throughout the life cycle of an asset Third is cycle time reduction. third is cycle time reduction Customer needs to move faster from planning to production. customer needs to move faster from planning to production From discovery to first oil and gas. from discovery to first oil and gas This requires technology and workflows that shorten project timelines, improve coordination, and accelerate decision-making across the value chain. The fourth is capital efficiency. Across all basins, our customers remain focused on cash flow and returns. They need more value from every dollar invested, and that requires solutions that improve productivity, reduce total cost of ownership, and deliver measurable impact at scale. Underpinning each of these priorities is a common enabler, AI and digital transformation. Increasingly, this is how performance will be achieved through better data, faster decision, and intelligent automation from planning to production. Customers expect equipment to be connected, workflows to be digital first, and decision to be informed by data. This is why the opportunity ahead is structural. Because even as the market continues to change, the need for energy and returns will not. Digital is key to both. This requires technology and workflows that shorten project timelines, improve coordination, and accelerate decision-making across the value chain. this requires technology and workflows that shorten project timelines improve coordination and accelerate decision-making across the value chain The fourth is capital efficiency. the fourth is capital efficiency Across all basins, our customers remain focused on cash flow and returns. across all basins our customers remain focused on cash flow and returns They need more value from every dollar invested, and that requires solutions that improve productivity, reduce total cost of ownership, and deliver measurable impact at scale. they need more value from every dollar invested and that requires solutions that improve productivity reduce total cost of ownership and deliver measurable impact at scale Underpinning each of these priorities is a common enabler, AI and digital transformation. underpinning each of these priorities is a common enabler ai and digital transformation Increasingly, this is how performance will be achieved through better data, faster decision, and intelligent automation from planning to production. increasingly this is how performance will be achieved through better data faster decision and intelligent automation from planning to production Customers expect equipment to be connected, workflows to be digital first, and decision to be informed by data. customers expect equipment to be connected workflows to be digital first and decision to be informed by data This is why the opportunity ahead is structural. this is why the opportunity ahead is structural Because even as the market continues to change, the need for energy and returns will not. because even as the market continues to change the need for energy and returns will not Digital is key to both. digital is key to both At SLB, we have been helping to shape the digital fabric of this industry for years. That matters because the capabilities our customer requires cannot be built overnight. They need trusted platform, proven workflows, and a partner that can deploy globally. Very few company can do this. We can. Our digital advantage is built across four reinforcing areas. Domain expertise, a platform approach, partnerships, and scale. It all starts with deep domain expertise. In our industry, you can't leave anything to chance. Decisions depend on a deep understanding of physics, the workflows, and the operational constraints. That expertise is embedded in our people, our models, and our platforms. It cannot be outsourced. It cannot be bought off the shelf, and it cannot be recreated by digital-only third-party provider. Second is our platform approach. Products create value, but platforms are what make them scale. At SLB, we have been helping to shape the digital fabric of this industry for years. at slb we have been helping to shape the digital fabric of this industry for years That matters because the capabilities our customer requires cannot be built overnight. that matters because the capabilities our customer requires cannot be built overnight They need trusted platform, proven workflows, and a partner that can deploy globally. they need trusted platform proven workflows and a partner that can deploy globally Very few company can do this. very few company can do this We can. we can Our digital advantage is built across four reinforcing areas. our digital advantage is built across four reinforcing areas Domain expertise, a platform approach, partnerships, and scale. domain expertise a platform approach partnerships and scale It all starts with deep domain expertise. it all starts with deep domain expertise In our industry, you can't leave anything to chance. in our industry you can't leave anything to chance Decisions depend on a deep understanding of physics, the workflows, and the operational constraints. decisions depend on a deep understanding of physics the workflows and the operational constraints That expertise is embedded in our people, our models, and our platforms. that expertise is embedded in our people our models and our platforms It cannot be outsourced. it cannot be outsourced It cannot be bought off the shelf, and it cannot be recreated by digital-only third-party provider. it cannot be bought off the shelf and it cannot be recreated by digital-only third-party provider Second is our platform approach. second is our platform approach Products create value, but platforms are what make them scale. products create value but platforms are what make them scale In the age of AI, platforms are becoming even more valuable because they are the control layer through which models, agents, and workflows operate together. This is why we have invested in architecture that is open and built to operate in environments our customer manage every day, from subsurface test planning to production operation, and from on-prem to the cloud. This wasn't built in a quarter. It was built over decades, and it is extremely difficult to replicate. Third, our partnerships. We work across operators, technology partners, and geographies to bring customers the best capability of the broader ecosystem to our platform. In digital, no company can do it alone. The key is knowing what to build, where to partner, and how to make those technologies work in the realities of an energy operation. This is what SLB does. In the age of AI, platforms are becoming even more valuable because they are the control layer through which models, agents, and workflows operate together. in the age of ai platforms are becoming even more valuable because they are the control layer through which models agents and workflows operate together This is why we have invested in architecture that is open and built to operate in environments our customer manage every day, from subsurface test planning to production operation, and from on-prem to the cloud. this is why we have invested in architecture that is open and built to operate in environments our customer manage every day from subsurface test planning to production operation and from on-prem to the cloud This wasn't built in a quarter. this wasn't built in a quarter It was built over decades, and it is extremely difficult to replicate. it was built over decades and it is extremely difficult to replicate Third, our partnerships. third our partnerships We work across operators, technology partners, and geographies to bring customers the best capability of the broader ecosystem to our platform. we work across operators technology partners and geographies to bring customers the best capability of the broader ecosystem to our platform In digital, no company can do it alone. in digital no company can do it alone The key is knowing what to build, where to partner, and how to make those technologies work in the realities of an energy operation. the key is knowing what to build where to partner and how to make those technologies work in the realities of an energy operation This is what SLB does. this is what slb does We connect leading technology with the data, science, and workflows of our industry to unlock performance and efficiency. Finally, our scale. SLB is funded across the major energy basins with the people, the infrastructure, and operational capability to support customers locally. That matters because digital and AI must work securely and reliably across all assets and operating environment. Our footprint allows us to learn globally, deploy locally, and extend what works across the energy system. This combination is what brings our AI advantage to life. Energy is among the most compelling environments for AI, with complex physics, high-value decision, and vast amounts of operational data. The technology is only as powerful as the data and the domain experts behind it. SLB has a unique ability to bring together platforms, connected assets, partner scale, and deep domain expertise. Individually, this capability matter. We connect leading technology with the data, science, and workflows of our industry to unlock performance and efficiency. we connect leading technology with the data science and workflows of our industry to unlock performance and efficiency Finally, our scale. finally our scale SLB is funded across the major energy basins with the people, the infrastructure, and operational capability to support customers locally. slb is funded across the major energy basins with the people the infrastructure and operational capability to support customers locally That matters because digital and AI must work securely and reliably across all assets and operating environment. that matters because digital and ai must work securely and reliably across all assets and operating environment Our footprint allows us to learn globally, deploy locally, and extend what works across the energy system. our footprint allows us to learn globally deploy locally and extend what works across the energy system This combination is what brings our AI advantage to life. this combination is what brings our ai advantage to life Energy is among the most compelling environments for AI, with complex physics, high-value decision, and vast amounts of operational data. energy is among the most compelling environments for ai with complex physics high-value decision and vast amounts of operational data The technology is only as powerful as the data and the domain experts behind it. the technology is only as powerful as the data and the domain experts behind it SLB has a unique ability to bring together platforms, connected assets, partner scale, and deep domain expertise. slb has a unique ability to bring together platforms connected assets partner scale and deep domain expertise Individually, this capability matter. individually this capability matter Together, they create a differential digital offering that is increasingly important and difficult to match. That is what we bring to our customers, and it is how SLB is taking digital and AI further. What does it mean in practice? It means we can go beyond software, collecting digital intelligence to hardware and sensors in the field so that insight become action and every decision improves the next. This is where science matters, where integration with all key technology makes an impact, and where our differentiation is the strongest. In planning, digital is already accelerating the prediction and improving model quality. AI can create a new growth curve in this market by automating workflows and personalizing our projects as they grow. In drilling, digital is enabling automation and real-time optimization. This lowers cost per mile. It accelerates access to resource, and it can significantly reduce the industry's carbon footprint. Together, they create a differential digital offering that is increasingly important and difficult to match. together they create a differential digital offering that is increasingly important and difficult to match That is what we bring to our customers, and it is how SLB is taking digital and AI further. that is what we bring to our customers and it is how slb is taking digital and ai further What does it mean in practice? what does it mean in practice It means we can go beyond software, collecting digital intelligence to hardware and sensors in the field so that insight become action and every decision improves the next. it means we can go beyond software collecting digital intelligence to hardware and sensors in the field so that insight become action and every decision improves the next This is where science matters, where integration with all key technology makes an impact, and where our differentiation is the strongest. this is where science matters where integration with all key technology makes an impact and where our differentiation is the strongest In planning, digital is already accelerating the prediction and improving model quality. in planning digital is already accelerating the prediction and improving model quality AI can create a new growth curve in this market by automating workflows and personalizing our projects as they grow. ai can create a new growth curve in this market by automating workflows and personalizing our projects as they grow In drilling, digital is enabling automation and real-time optimization. in drilling digital is enabling automation and real-time optimization This lowers cost per mile. this lowers cost per mile It accelerates access to resource, and it can significantly reduce the industry's carbon footprint. it accelerates access to resource and it can significantly reduce the industry's carbon footprint In production, digital is increasing uptime by predicting issues before they occur. This cuts maintenance costs and extends asset life. It also optimize the reservoir production potential. These example are here, and they are happening today, and you will hear throughout this presentation this morning. Moving forward, as the industry advance more autonomous operation, customer will simplify who they work with, prioritizing partners who can deliver across the full ecosystem. That dynamic strengthens our core business, creates new revenue opportunities, and expand the strategic value of our platform. This is how digital drives growth, not only within digital itself, but increasingly across all of SLB as we move from being first in digital to becoming digital first. Across every well, every mile, every customer. This is not only a secondary story. It is a growth story. It is a margin story and a return story. In production, digital is increasing uptime by predicting issues before they occur. in production digital is increasing uptime by predicting issues before they occur This cuts maintenance costs and extends asset life. this cuts maintenance costs and extends asset life It also optimize the reservoir production potential. it also optimize the reservoir production potential These example are here, and they are happening today, and you will hear throughout this presentation this morning. these example are here and they are happening today and you will hear throughout this presentation this morning Moving forward, as the industry advance more autonomous operation, customer will simplify who they work with, prioritizing partners who can deliver across the full ecosystem. moving forward as the industry advance more autonomous operation customer will simplify who they work with prioritizing partners who can deliver across the full ecosystem That dynamic strengthens our core business, creates new revenue opportunities, and expand the strategic value of our platform. that dynamic strengthens our core business creates new revenue opportunities and expand the strategic value of our platform This is how digital drives growth, not only within digital itself, but increasingly across all of SLB as we move from being first in digital to becoming digital first. this is how digital drives growth not only within digital itself but increasingly across all of slb as we move from being first in digital to becoming digital first Across every well, every mile, every customer. across every well every mile every customer This is not only a secondary story. this is not only a secondary story It is a growth story. it is a growth story It is a margin story and a return story. it is a margin story and a return story Digital is already a powerful earnings engine for SLB. For every $1 of revenue, digital generates 1.5x the adjusted EBITDA compared to the rest of our portfolio. This is also one of the fastest-growing parts of our business, and its margins have continued to expand over time. The value of digital extends beyond the segment itself. This technology are increasingly embedded in the rest of our portfolio, helping customer move faster, produce more efficiently, and recover more from existing assets. When our customer perform better, SLB becomes more valuable to them, increasing retention and expanding our total addressable market. The story is not simply digital as a division. The story is how digital lifts the earnings power of the entire company. This is a far larger opportunity, and today you will hear how we plan to capture it. Digital is already a powerful earnings engine for SLB. digital is already a powerful earnings engine for slb For every $1 of revenue, digital generates 1.5x the adjusted EBITDA compared to the rest of our portfolio. for every $1 of revenue digital generates 1.5x the adjusted ebitda compared to the rest of our portfolio This is also one of the fastest-growing parts of our business, and its margins have continued to expand over time. this is also one of the fastest-growing parts of our business and its margins have continued to expand over time The value of digital extends beyond the segment itself. the value of digital extends beyond the segment itself This technology are increasingly embedded in the rest of our portfolio, helping customer move faster, produce more efficiently, and recover more from existing assets. this technology are increasingly embedded in the rest of our portfolio helping customer move faster produce more efficiently and recover more from existing assets When our customer perform better, SLB becomes more valuable to them, increasing retention and expanding our total addressable market. when our customer perform better slb becomes more valuable to them increasing retention and expanding our total addressable market The story is not simply digital as a division. the story is not simply digital as a division The story is how digital lifts the earnings power of the entire company. the story is how digital lifts the earnings power of the entire company This is a far larger opportunity, and today you will hear how we plan to capture it. this is a far larger opportunity and today you will hear how we plan to capture it Throughout this morning, our leadership team takes you deeper into the opportunity, the strategy, the financial frameworks behind this business. First, you hear about our flagship platforms, comprehensive digital offering and competitive advantage. You will see why our position is strengthening as adoption scales and why our platform becomes more valuable as customers move from digital pilots to enterprise-wide deployment. You'll hear about the race to scale digital operation and AI. This is where applications, connected equipment, automation, and AI come together to transform how we sense and manage in real time, and we believe this can become an important new growth engine at SLB. Finally, we discuss key performance indicators. This time, how we are monetizing significant opportunities ahead and share our 2030 financial ambitions for this business. As you listen, I encourage you to keep this in mind. Throughout this morning, our leadership team takes you deeper into the opportunity, the strategy, the financial frameworks behind this business. throughout this morning our leadership team takes you deeper into the opportunity the strategy the financial frameworks behind this business First, you hear about our flagship platforms, comprehensive digital offering and competitive advantage. first you hear about our flagship platforms comprehensive digital offering and competitive advantage You will see why our position is strengthening as adoption scales and why our platform becomes more valuable as customers move from digital pilots to enterprise-wide deployment. you will see why our position is strengthening as adoption scales and why our platform becomes more valuable as customers move from digital pilots to enterprise-wide deployment You'll hear about the race to scale digital operation and AI. you'll hear about the race to scale digital operation and ai This is where applications, connected equipment, automation, and AI come together to transform how we sense and manage in real time, and we believe this can become an important new growth engine at SLB. this is where applications connected equipment automation and ai come together to transform how we sense and manage in real time and we believe this can become an important new growth engine at slb Finally, we discuss key performance indicators. finally we discuss key performance indicators This time, how we are monetizing significant opportunities ahead and share our 2030 financial ambitions for this business. this time how we are monetizing significant opportunities ahead and share our 2030 financial ambitions for this business As you listen, I encourage you to keep this in mind. as you listen i encourage you to keep this in mind Digital is becoming central to how this industry drives performance, unlocks efficiency, and creates value. With our platforms, domain expertise, and global scale, SLB is well-positioned to lead this next chapter. Thank you again for being here with us. We're excited to share the momentum we have built and the opportunities ahead. Before I welcome Rakesh to the stage, let's hear from some industry leaders as they share their own perspective on SLB's contribution to their digital journeys. Digital is becoming central to how this industry drives performance, unlocks efficiency, and creates value. digital is becoming central to how this industry drives performance unlocks efficiency and creates value With our platforms, domain expertise, and global scale, SLB is well-positioned to lead this next chapter. with our platforms domain expertise and global scale slb is well-positioned to lead this next chapter Thank you again for being here with us. thank you again for being here with us We're excited to share the momentum we have built and the opportunities ahead. we're excited to share the momentum we have built and the opportunities ahead Before I welcome Rakesh to the stage, let's hear from some industry leaders as they share their own perspective on SLB's contribution to their digital journeys. before i welcome rakesh to the stage let's hear from some industry leaders as they share their own perspective on slb's contribution to their digital journeys

Speaker 27: In 2019, Chevron, SLB, and Microsoft formed a strategic collaboration to accelerate petrotechnical digital solutions anchored in the Delfi platform. By combining a century of SLB's domain experience with Microsoft's cloud infrastructure and Chevron's experience and operating scale, we've moved from pilot to measurable performance, delivering sustained value across our global operations. In 2019, Chevron, SLB, and Microsoft formed a strategic collaboration to accelerate petrotechnical digital solutions anchored in the Delfi platform. in 2019 chevron slb and microsoft formed a strategic collaboration to accelerate petrotechnical digital solutions anchored in the delfi platform By combining a century of SLB's domain experience with Microsoft's cloud infrastructure and Chevron's experience and operating scale, we've moved from pilot to measurable performance, delivering sustained value across our global operations. by combining a century of slb's domain experience with microsoft's cloud infrastructure and chevron's experience and operating scale we've moved from pilot to measurable performance delivering sustained value across our global operations Together with SLB's continued commitment to innovation, that's positioned them strongly to build and deploy secure, agentic workflows that are disruptive to our industry. Together with SLB's continued commitment to innovation, that's positioned them strongly to build and deploy secure, agentic workflows that are disruptive to our industry. together with slb's continued commitment to innovation that's positioned them strongly to build and deploy secure agentic workflows that are disruptive to our industry

Speaker 24: One of the main leverages that we need to use is artificial intelligence and digital. In order to do that, we've decided to partner with SLB on a partnership on subsurface called Arena. It's a 10-year partnership which couples the know-how of our reservoir engineers, along with the digital and AI capabilities of SLB. One of the main leverages that we need to use is artificial intelligence and digital. one of the main leverages that we need to use is artificial intelligence and digital In order to do that, we've decided to partner with SLB on a partnership on subsurface called Arena. in order to do that we've decided to partner with slb on a partnership on subsurface called arena It's a 10-year partnership which couples the know-how of our reservoir engineers, along with the digital and AI capabilities of SLB. it's a 10-year partnership which couples the know-how of our reservoir engineers along with the digital and ai capabilities of slb The SLB Delfi digital platform allows us to seamlessly integrate subsurface evaluation, well planning, and field development, enhancing collaboration, enabling our teams to work concurrently rather than sequentially. As a result, we shorten planning cycles from months to days, significantly accelerating time from discovery to first production. The SLB Delfi digital platform allows us to seamlessly integrate subsurface evaluation, well planning, and field development, enhancing collaboration, enabling our teams to work concurrently rather than sequentially. the slb delfi digital platform allows us to seamlessly integrate subsurface evaluation well planning and field development enhancing collaboration enabling our teams to work concurrently rather than sequentially As a result, we shorten planning cycles from months to days, significantly accelerating time from discovery to first production. as a result we shorten planning cycles from months to days significantly accelerating time from discovery to first production A key part of our 2024 strategy is to implement and maintain world-class standards of operational excellence by embedding digital intelligence with SLB and partners. We are well on the way to achieving this with AI initiatives running across the full E&P value chain. A key part of our 2024 strategy is to implement and maintain world-class standards of operational excellence by embedding digital intelligence with SLB and partners. a key part of our 2024 strategy is to implement and maintain world-class standards of operational excellence by embedding digital intelligence with slb and partners We are well on the way to achieving this with AI initiatives running across the full E&P value chain. we are well on the way to achieving this with ai initiatives running across the full e&p value chain

Speaker 15: Wow. I've seen this video multiple times, every time I see this video, I feel that we're onto something. What the future holds for us gets me even more excited. Of course, we are very grateful for these messages, and a big thank you to all our customers who challenge us to go further every day. I'm Rakesh Jaggi, and I have the privilege of running the digital business at SLB. Along with Trygve Randen, the Senior Vice President of Digital Products and Solutions, we will highlight SLB's unique and compounding advantage at the exciting intersection of digital and energy. Before I go there, allow me to take you on a tour through the upstream value chain. These are the big questions our customers must answer. We start by asking, "Where should I look for oil and gas? Wow. wow I've seen this video multiple times, every time I see this video, I feel that we're onto something. i've seen this video multiple times every time i see this video i feel that we're onto something What the future holds for us gets me even more excited. what the future holds for us gets me even more excited Of course, we are very grateful for these messages, and a big thank you to all our customers who challenge us to go further every day. of course we are very grateful for these messages and a big thank you to all our customers who challenge us to go further every day I'm Rakesh Jaggi, and I have the privilege of running the digital business at SLB. i'm rakesh jaggi and i have the privilege of running the digital business at slb Along with Trygve Randen, the Senior Vice President of Digital Products and Solutions, we will highlight SLB's unique and compounding advantage at the exciting intersection of digital and energy. along with trygve randen the senior vice president of digital products and solutions we will highlight slb's unique and compounding advantage at the exciting intersection of digital and energy Before I go there, allow me to take you on a tour through the upstream value chain. before i go there allow me to take you on a tour through the upstream value chain These are the big questions our customers must answer. these are the big questions our customers must answer We start by asking, "Where should I look for oil and gas? we start by asking "where should i look for oil and gas Which basins and geologies offer the best potential for discovery and extraction of commercially viable hydrocarbons? How do I allocate capital across frontier exploration, proven undeveloped resources, and also the aging fields I have in my portfolio? How do I ensure that every asset is producing at its full potential, that I'm leaving nothing in the ground and nothing on the table? Most importantly, how do I operate safely and efficiently across a complex hardware landscape where a single failure can be catastrophic, where decisions cannot be left to chance, because in our industry, probably right is absolutely wrong?" These are some of the questions that define the upstream oil and gas, getting answers to these questions takes us right to the heart of our digital offering. Which basins and geologies offer the best potential for discovery and extraction of commercially viable hydrocarbons? which basins and geologies offer the best potential for discovery and extraction of commercially viable hydrocarbons How do I allocate capital across frontier exploration, proven undeveloped resources, and also the aging fields I have in my portfolio? how do i allocate capital across frontier exploration proven undeveloped resources and also the aging fields i have in my portfolio How do I ensure that every asset is producing at its full potential, that I'm leaving nothing in the ground and nothing on the table? how do i ensure that every asset is producing at its full potential that i'm leaving nothing in the ground and nothing on the table Most importantly, how do I operate safely and efficiently across a complex hardware landscape where a single failure can be catastrophic, where decisions cannot be left to chance, because in our industry, probably right is absolutely wrong?" These are some of the questions that define the upstream oil and gas, getting answers to these questions takes us right to the heart of our digital offering. most importantly how do i operate safely and efficiently across a complex hardware landscape where a single failure can be catastrophic where decisions cannot be left to chance because in our industry probably right is absolutely wrong?" these are some of the questions that define the upstream oil and gas getting answers to these questions takes us right to the heart of our digital offering Our ability to serve the upstream market rests on four areas of differentiation. Each of them position us uniquely, but taken together, they represent a wide and deep moat. I know Olivier already introduced these in his opening presentation this morning, but I'd like to take you a level deeper. The first is domain expertise. SLB has spent a century measuring, modeling, and interpreting the subsurface. That science is not peripheral to our digital business. It is the very foundation of it. It is encoded in our software and embedded in the data on which our models are trained. The second is platforms. We have built and commercialized enterprise-grade cloud-native platforms, Delfi for workflows and Lumi for data and AI. These are purpose-built for our industry. They are designed for the specific data types, security and uptime requirements, and scientific workflows that the upstream operators depend on. Our ability to serve the upstream market rests on four areas of differentiation. our ability to serve the upstream market rests on four areas of differentiation Each of them position us uniquely, but taken together, they represent a wide and deep moat. each of them position us uniquely but taken together they represent a wide and deep moat I know Olivier already introduced these in his opening presentation this morning, but I'd like to take you a level deeper. i know olivier already introduced these in his opening presentation this morning but i'd like to take you a level deeper The first is domain expertise. the first is domain expertise SLB has spent a century measuring, modeling, and interpreting the subsurface. slb has spent a century measuring modeling and interpreting the subsurface That science is not peripheral to our digital business. that science is not peripheral to our digital business It is the very foundation of it. it is the very foundation of it It is encoded in our software and embedded in the data on which our models are trained. it is encoded in our software and embedded in the data on which our models are trained The second is platforms. the second is platforms We have built and commercialized enterprise-grade cloud-native platforms, Delfi for workflows and Lumi for data and AI. we have built and commercialized enterprise-grade cloud-native platforms delfi for workflows and lumi for data and ai These are purpose-built for our industry. these are purpose-built for our industry They are designed for the specific data types, security and uptime requirements, and scientific workflows that the upstream operators depend on. they are designed for the specific data types security and uptime requirements and scientific workflows that the upstream operators depend on Trygve will give you a more in-depth look at our technology stack and why is it that it is so special. The third differentiation is partners. Our platforms are open and host a best-in-class tech ecosystem. We are deliberate about what we build and what we integrate. Cloud infrastructure from the leading hyperscalers, operational data capability and AI tooling from specialized technology players, large language models or LLMs from leading AI providers. Our platforms are enriched by the technology of others in areas where we choose not to compete. You will hear directly from some of these partners in a bit. The fourth key area of differentiation is scale. In many ways, it is the outcome of the other three. Trygve will give you a more in-depth look at our technology stack and why is it that it is so special. trygve will give you a more in-depth look at our technology stack and why is it that it is so special The third differentiation is partners. the third differentiation is partners Our platforms are open and host a best-in-class tech ecosystem. our platforms are open and host a best-in-class tech ecosystem We are deliberate about what we build and what we integrate. we are deliberate about what we build and what we integrate Cloud infrastructure from the leading hyperscalers, operational data capability and AI tooling from specialized technology players, large language models or LLMs from leading AI providers. cloud infrastructure from the leading hyperscalers operational data capability and ai tooling from specialized technology players large language models or llms from leading ai providers Our platforms are enriched by the technology of others in areas where we choose not to compete. our platforms are enriched by the technology of others in areas where we choose not to compete You will hear directly from some of these partners in a bit. you will hear directly from some of these partners in a bit The fourth key area of differentiation is scale. the fourth key area of differentiation is scale In many ways, it is the outcome of the other three. in many ways it is the outcome of the other three Domain expertise gives us the right to play, platforms give us the means to deliver, partners give us the speed to market, scale allows us to deliver for our customers across all geographies and resource plays. These four areas, domain, platform, partners, and scale, are mutually reinforcing. They allow us to compete in a way that other technology companies or traditional oil field services and equipment companies cannot. All of this did not happen overnight. SLB has a history of disruption embedded in our DNA. We began collecting computer-ready data in the field in 1952. Since then, we have seen a succession of technology shifts from mainframe to workstations to personal computers, then onto the cloud. With each of these shifts, we deployed the same playbook. Domain expertise gives us the right to play, platforms give us the means to deliver, partners give us the speed to market, scale allows us to deliver for our customers across all geographies and resource plays. domain expertise gives us the right to play platforms give us the means to deliver partners give us the speed to market scale allows us to deliver for our customers across all geographies and resource plays These four areas, domain, platform, partners, and scale, are mutually reinforcing. these four areas domain platform partners and scale are mutually reinforcing They allow us to compete in a way that other technology companies or traditional oil field services and equipment companies cannot. they allow us to compete in a way that other technology companies or traditional oil field services and equipment companies cannot All of this did not happen overnight. all of this did not happen overnight SLB has a history of disruption embedded in our DNA. slb has a history of disruption embedded in our dna We began collecting computer-ready data in the field in 1952. we began collecting computer-ready data in the field in 1952 Since then, we have seen a succession of technology shifts from mainframe to workstations to personal computers, then onto the cloud. since then we have seen a succession of technology shifts from mainframe to workstations to personal computers then onto the cloud With each of these shifts, we deployed the same playbook. with each of these shifts we deployed the same playbook Each time a new computing architecture emerges, we use it not only to modernize the existing tools, but to fundamentally expand what our customers can do. Another shift is underway, this, ladies and gentlemen, is truly different. Artificial intelligence isn't just changing how software is delivered and consumed. It promises to be the most fundamental and revolutionary shift we've ever seen. agentic AI, in particular, changes what software can do. With agentic AI, we are creating systems that observe, reason, act, and learn. Dare I say that while others have been fast followers, when it comes to our digital capabilities, we've always been first. Just two weeks ago, as some of you would have noticed, the AI-Driven Enterprise Institute awarded SLB a perfect score for AI adoption. A score achieved by only three other companies, NVIDIA, Amazon, and Meta. Each time a new computing architecture emerges, we use it not only to modernize the existing tools, but to fundamentally expand what our customers can do. each time a new computing architecture emerges we use it not only to modernize the existing tools but to fundamentally expand what our customers can do Another shift is underway, this, ladies and gentlemen, is truly different. another shift is underway this ladies and gentlemen is truly different Artificial intelligence isn't just changing how software is delivered and consumed. artificial intelligence isn't just changing how software is delivered and consumed It promises to be the most fundamental and revolutionary shift we've ever seen. agentic AI, in particular, changes what software can do. it promises to be the most fundamental and revolutionary shift we've ever seen agentic ai in particular changes what software can do With agentic AI, we are creating systems that observe, reason, act, and learn. with agentic ai we are creating systems that observe reason act and learn Dare I say that while others have been fast followers, when it comes to our digital capabilities, we've always been first. dare i say that while others have been fast followers when it comes to our digital capabilities we've always been first Just two weeks ago, as some of you would have noticed, the AI-Driven Enterprise Institute awarded SLB a perfect score for AI adoption. just two weeks ago as some of you would have noticed the ai-driven enterprise institute awarded slb a perfect score for ai adoption A score achieved by only three other companies, NVIDIA, Amazon, and Meta. a score achieved by only three other companies nvidia amazon and meta We are a company whose entire digital history has been converging on this moment, where domain science, trusted data, and intelligent systems meet in a single stack. I want to give you an analogy. The banking sector has undergone a very similar journey. The way my father banks, and God bless his soul, he's going to turn 92 day after tomorrow, and the way I bank are very different. The banking sector, three to four decades ago, decided to digitize each of the steps that required a customer to visit the bank. I don't remember the last time I went to the bank. This is exactly what we have done for our industry. Let me illustrate how our domain applications help our customers along the industry value chain, just like the banking sector. We are a company whose entire digital history has been converging on this moment, where domain science, trusted data, and intelligent systems meet in a single stack. we are a company whose entire digital history has been converging on this moment where domain science trusted data and intelligent systems meet in a single stack I want to give you an analogy. i want to give you an analogy The banking sector has undergone a very similar journey. the banking sector has undergone a very similar journey The way my father banks, and God bless his soul, he's going to turn 92 day after tomorrow, and the way I bank are very different. the way my father banks and god bless his soul he's going to turn 92 day after tomorrow and the way i bank are very different The banking sector, three to four decades ago, decided to digitize each of the steps that required a customer to visit the bank. the banking sector three to four decades ago decided to digitize each of the steps that required a customer to visit the bank I don't remember the last time I went to the bank. i don't remember the last time i went to the bank This is exactly what we have done for our industry. this is exactly what we have done for our industry Let me illustrate how our domain applications help our customers along the industry value chain, just like the banking sector. let me illustrate how our domain applications help our customers along the industry value chain just like the banking sector All of our domain offerings can be classified in two broad categories: planning and operations. There are steps that you have to take to get to your destination as a petrotechnical or operational expert. We have a product that will help our customers perform each of these steps digitally. We do not want them to work manually like my father did decades ago. They never have to bring manual skills to bear if the job can be done successfully, more efficiently, and more accurately by software. Let me go through the steps a petrotechnical expert undertakes in the planning phase. The workflow in planning begins with raw seismic data. This is the aggregation of sound waves that are sent into the Earth and reflected back. It's transforming billions of acoustic signals into a usable image of the subsurface. Think of it like the MRI scan of the Earth. All of our domain offerings can be classified in two broad categories: planning and operations. all of our domain offerings can be classified in two broad categories planning and operations There are steps that you have to take to get to your destination as a petrotechnical or operational expert. there are steps that you have to take to get to your destination as a petrotechnical or operational expert We have a product that will help our customers perform each of these steps digitally. we have a product that will help our customers perform each of these steps digitally We do not want them to work manually like my father did decades ago. we do not want them to work manually like my father did decades ago They never have to bring manual skills to bear if the job can be done successfully, more efficiently, and more accurately by software. they never have to bring manual skills to bear if the job can be done successfully more efficiently and more accurately by software Let me go through the steps a petrotechnical expert undertakes in the planning phase. let me go through the steps a petrotechnical expert undertakes in the planning phase The workflow in planning begins with raw seismic data. the workflow in planning begins with raw seismic data This is the aggregation of sound waves that are sent into the Earth and reflected back. this is the aggregation of sound waves that are sent into the earth and reflected back It's transforming billions of acoustic signals into a usable image of the subsurface. it's transforming billions of acoustic signals into a usable image of the subsurface Think of it like the MRI scan of the Earth. think of it like the mri scan of the earth Geophysical interpretation maps the layers and faults. Structural modeling and well interpretation then reveal how subsurface layers were formed and enable us to construct a 3D model of the subsurface. Reservoir and geological modeling predict properties like porosity and permeability and identify where hydrocarbons are likely to accumulate. Reservoir engineering quantifies the flow of fluids through rock formations and how the field will produce over time, incorporating the surface infrastructure into that equation, too. Next, field development planning or FDP comes in. Every technical step is overlaid with economic considerations, oil prices, capital outlay, operating costs, each element with its own uncertainties. Field development planning determines the returns to access the hydrocarbons underground. What you've just seen is a whirlwind tour of what a petrotechnical expert lives daily. We have an application for each of these steps. Omega, Petrel, Techlog, Intersect, FD Plan. Geophysical interpretation maps the layers and faults. geophysical interpretation maps the layers and faults Structural modeling and well interpretation then reveal how subsurface layers were formed and enable us to construct a 3D model of the subsurface. structural modeling and well interpretation then reveal how subsurface layers were formed and enable us to construct a 3d model of the subsurface Reservoir and geological modeling predict properties like porosity and permeability and identify where hydrocarbons are likely to accumulate. reservoir and geological modeling predict properties like porosity and permeability and identify where hydrocarbons are likely to accumulate Reservoir engineering quantifies the flow of fluids through rock formations and how the field will produce over time, incorporating the surface infrastructure into that equation, too. reservoir engineering quantifies the flow of fluids through rock formations and how the field will produce over time incorporating the surface infrastructure into that equation too Next, field development planning or FDP comes in. next field development planning or fdp comes in Every technical step is overlaid with economic considerations, oil prices, capital outlay, operating costs, each element with its own uncertainties. every technical step is overlaid with economic considerations oil prices capital outlay operating costs each element with its own uncertainties Field development planning determines the returns to access the hydrocarbons underground. field development planning determines the returns to access the hydrocarbons underground What you've just seen is a whirlwind tour of what a petrotechnical expert lives daily. what you've just seen is a whirlwind tour of what a petrotechnical expert lives daily We have an application for each of these steps. we have an application for each of these steps Omega, Petrel, Techlog, Intersect, FD Plan. omega petrel techlog intersect fd plan These offerings enable our customers to complete their work anytime, anywhere, across every stage of the planning process. Once a development is sanctioned, the focus must shift to operations. Drilling planning is where operators engineer the well that will access the reservoir, defining trajectory for every section of that well. Drilling operations is execution of that plan, managing the real-time complexity of putting a wellbore through thousands of meters of rock. Production operations is the management of flowing wells and production networks. It includes the optimization of hydrocarbons to the surface. For aging fields with declining pressure, artificial lift is employed. Asset performance then encompasses the surface infrastructure, including facilities, processing equipment, pipelines, et cetera, that must operate continuously because unplanned downtime has consequences measured in millions of dollars a day. What we just saw is a quick tour of the operations. These offerings enable our customers to complete their work anytime, anywhere, across every stage of the planning process. these offerings enable our customers to complete their work anytime anywhere across every stage of the planning process Once a development is sanctioned, the focus must shift to operations. once a development is sanctioned the focus must shift to operations Drilling planning is where operators engineer the well that will access the reservoir, defining trajectory for every section of that well. drilling planning is where operators engineer the well that will access the reservoir defining trajectory for every section of that well Drilling operations is execution of that plan, managing the real-time complexity of putting a wellbore through thousands of meters of rock. drilling operations is execution of that plan managing the real-time complexity of putting a wellbore through thousands of meters of rock Production operations is the management of flowing wells and production networks. production operations is the management of flowing wells and production networks It includes the optimization of hydrocarbons to the surface. it includes the optimization of hydrocarbons to the surface For aging fields with declining pressure, artificial lift is employed. for aging fields with declining pressure artificial lift is employed Asset performance then encompasses the surface infrastructure, including facilities, processing equipment, pipelines, et cetera, that must operate continuously because unplanned downtime has consequences measured in millions of dollars a day. asset performance then encompasses the surface infrastructure including facilities processing equipment pipelines et cetera that must operate continuously because unplanned downtime has consequences measured in millions of dollars a day What we just saw is a quick tour of the operations. what we just saw is a quick tour of the operations DrillOps, OptiFlow, OptiLift, OptiSite, powered by our Agora edge AI platform. Just as in planning, SLB Digital is increasingly serving each of these core operating processes, too. We are uniquely present across the entire value chain, from exploration through development and production, both in planning and operations from the edge to the office. I'm sure my daughters would like to bank differently compared to me, and we too are preparing for the agentic AI future for our industry. Besides planning and operations, we also have a market segment of data and AI. This framework on the slide now will provide insights into a key part of our digital strategy. If planning and operations are where the decisions are made, the data layer is where the raw materials for those decisions is organized and made accessible. Upstream operations generate extraordinary volumes of data. DrillOps, OptiFlow, OptiLift, OptiSite, powered by our Agora edge AI platform. drillops optiflow optilift optisite powered by our agora edge ai platform Just as in planning, SLB Digital is increasingly serving each of these core operating processes, too. just as in planning slb digital is increasingly serving each of these core operating processes too We are uniquely present across the entire value chain, from exploration through development and production, both in planning and operations from the edge to the office. we are uniquely present across the entire value chain from exploration through development and production both in planning and operations from the edge to the office I'm sure my daughters would like to bank differently compared to me, and we too are preparing for the agentic AI future for our industry. i'm sure my daughters would like to bank differently compared to me and we too are preparing for the agentic ai future for our industry Besides planning and operations, we also have a market segment of data and AI. besides planning and operations we also have a market segment of data and ai This framework on the slide now will provide insights into a key part of our digital strategy. this framework on the slide now will provide insights into a key part of our digital strategy If planning and operations are where the decisions are made, the data layer is where the raw materials for those decisions is organized and made accessible. if planning and operations are where the decisions are made the data layer is where the raw materials for those decisions is organized and made accessible Upstream operations generate extraordinary volumes of data. upstream operations generate extraordinary volumes of data A single deep water well through its lifetime will generate around 10 petabytes of data, which is equivalent to nearly half a million of the 4K movies that you and I enjoy. This is a distinct and new market with new buyers for us. I've described planning and operations as two different worlds. As many of you would have already guessed, there is huge value in bringing them together, our digital tools make that possible today. Connecting these worlds for data is what SLB's Lumi and data and AI platform makes possible. It is a single trusted layer which connects planning data to the operations data seamlessly. Just like the banking sector, the Delfi platform has digitized the workflows for both planning and operations on the cloud. A single deep water well through its lifetime will generate around 10 petabytes of data, which is equivalent to nearly half a million of the 4K movies that you and I enjoy. a single deep water well through its lifetime will generate around 10 petabytes of data which is equivalent to nearly half a million of the 4k movies that you and i enjoy This is a distinct and new market with new buyers for us. this is a distinct and new market with new buyers for us I've described planning and operations as two different worlds. i've described planning and operations as two different worlds As many of you would have already guessed, there is huge value in bringing them together, our digital tools make that possible today. as many of you would have already guessed there is huge value in bringing them together our digital tools make that possible today Connecting these worlds for data is what SLB's Lumi and data and AI platform makes possible. connecting these worlds for data is what slb's lumi and data and ai platform makes possible It is a single trusted layer which connects planning data to the operations data seamlessly. it is a single trusted layer which connects planning data to the operations data seamlessly Just like the banking sector, the Delfi platform has digitized the workflows for both planning and operations on the cloud. just like the banking sector the delfi platform has digitized the workflows for both planning and operations on the cloud We are the only company that plays in all three of these market segments, planning, operations, and data and AI. The value we generate is clear. In planning, we reduce cycle time and risk. In operations, we enable greater production and superior efficiency. With Lumi, we help unleash the power of AI. Data from operations helps us plan better, which optimizes future operations. This becomes an exponential loop, bringing significant improvements in efficiency. From a commercial perspective, this is the flywheel that drives our commercial model too. More integrated workflows means more platform usage. Richer data means more AI workloads. Better AI means customers do more analysis, run more scenarios, deploy more agents. The circle turns, and with every rotation, the outcomes improve for our customers, and the value of our partnership deepens. We are the only company that plays in all three of these market segments, planning, operations, and data and AI. we are the only company that plays in all three of these market segments planning operations and data and ai The value we generate is clear. the value we generate is clear In planning, we reduce cycle time and risk. in planning we reduce cycle time and risk In operations, we enable greater production and superior efficiency. in operations we enable greater production and superior efficiency With Lumi, we help unleash the power of AI. with lumi we help unleash the power of ai Data from operations helps us plan better, which optimizes future operations. data from operations helps us plan better which optimizes future operations This becomes an exponential loop, bringing significant improvements in efficiency. this becomes an exponential loop bringing significant improvements in efficiency From a commercial perspective, this is the flywheel that drives our commercial model too. from a commercial perspective this is the flywheel that drives our commercial model too More integrated workflows means more platform usage. more integrated workflows means more platform usage Richer data means more AI workloads. richer data means more ai workloads Better AI means customers do more analysis, run more scenarios, deploy more agents. better ai means customers do more analysis run more scenarios deploy more agents The circle turns, and with every rotation, the outcomes improve for our customers, and the value of our partnership deepens. the circle turns and with every rotation the outcomes improve for our customers and the value of our partnership deepens Finally, let me put this in a context that will speak to all of you. To illustrate this, I will use Microsoft's product architecture as a comparison. We all know about the Microsoft stack, with tools like Word, Excel, and PowerPoint. You're also aware of the OneDrive and how you access and share files in your organization. Petrel, Techlog, DrillPlan, and OptiFlow are applications just like Word, Excel, and PowerPoint. Delfi is the Office 365 equivalent that binds them together architecturally and commercially in a cloud-native digital platform. It is the environment which our planning and operation software is accessed. Petrel, Techlog, DrillPlan, OptiFlow, all delivered through a single secure experience. Delfi is more than a hosting layer. It is an integration environment, the place where decisions flow between disciplines without manual handoffs. Finally, let me put this in a context that will speak to all of you. finally let me put this in a context that will speak to all of you To illustrate this, I will use Microsoft's product architecture as a comparison. to illustrate this i will use microsoft's product architecture as a comparison We all know about the Microsoft stack, with tools like Word, Excel, and PowerPoint. we all know about the microsoft stack with tools like word excel and powerpoint You're also aware of the OneDrive and how you access and share files in your organization. you're also aware of the onedrive and how you access and share files in your organization Petrel, Techlog, DrillPlan, and OptiFlow are applications just like Word, Excel, and PowerPoint. petrel techlog drillplan and optiflow are applications just like word excel and powerpoint Delfi is the Office 365 equivalent that binds them together architecturally and commercially in a cloud-native digital platform. delfi is the office 365 equivalent that binds them together architecturally and commercially in a cloud-native digital platform It is the environment which our planning and operation software is accessed. it is the environment which our planning and operation software is accessed Petrel, Techlog, DrillPlan, OptiFlow, all delivered through a single secure experience. petrel techlog drillplan optiflow all delivered through a single secure experience Delfi is more than a hosting layer. delfi is more than a hosting layer It is an integration environment, the place where decisions flow between disciplines without manual handoffs. it is an integration environment the place where decisions flow between disciplines without manual handoffs A subsurface model built by a geoscientist in Petrel can be consumed directly by a drilling engineer in DrillPlan. Real-time production data in OptiFlow can feed back into a reservoir simulation in Intersect. The transition from planning to operations that we described earlier, that seamless handoff between the work of deciding where to drill and the physical work of actually drilling that well, Delfi is where that becomes real. Lumi is our data and AI infrastructure, just like OneDrive and Azure AI Foundry is for Microsoft. If Delfi is where workflows run, Lumi provides the scalable, governed environment to ingest, contextualize, and deliver the data so that the right data in the right shape reaches the right workflow at the right time. It is also the home of our agentic AI workflow. A subsurface model built by a geoscientist in Petrel can be consumed directly by a drilling engineer in DrillPlan. a subsurface model built by a geoscientist in petrel can be consumed directly by a drilling engineer in drillplan Real-time production data in OptiFlow can feed back into a reservoir simulation in Intersect. real-time production data in optiflow can feed back into a reservoir simulation in intersect The transition from planning to operations that we described earlier, that seamless handoff between the work of deciding where to drill and the physical work of actually drilling that well, Delfi is where that becomes real. the transition from planning to operations that we described earlier that seamless handoff between the work of deciding where to drill and the physical work of actually drilling that well delfi is where that becomes real Lumi is our data and AI infrastructure, just like OneDrive and Azure AI Foundry is for Microsoft. lumi is our data and ai infrastructure just like onedrive and azure ai foundry is for microsoft If Delfi is where workflows run, Lumi provides the scalable, governed environment to ingest, contextualize, and deliver the data so that the right data in the right shape reaches the right workflow at the right time. if delfi is where workflows run lumi provides the scalable governed environment to ingest contextualize and deliver the data so that the right data in the right shape reaches the right workflow at the right time It is also the home of our agentic AI workflow. it is also the home of our agentic ai workflow We have things like domain foundation models, our agentic AI framework, and digital twins as a part of it as well. Working in sync across both Delfi and Lumi is Tela, our agentic AI, the parallel is Copilot in Microsoft. Shashi will elaborate on this exciting technology later. Briefly put, Tela is an agentic AI mesh that operates within the workflows and data environments our customers already use. Its architecture follows a continuous loop: observe, plan, generate, act, and learn. It is grounded in domain models and industry-specific guardrails that SLB has built. Before I hand it to Trygve to share more details on our platform approach, let's hear from a key customer in the Middle East. We have things like domain foundation models, our agentic AI framework, and digital twins as a part of it as well. we have things like domain foundation models our agentic ai framework and digital twins as a part of it as well Working in sync across both Delfi and Lumi is Tela, our agentic AI, the parallel is Copilot in Microsoft. working in sync across both delfi and lumi is tela our agentic ai the parallel is copilot in microsoft Shashi will elaborate on this exciting technology later. shashi will elaborate on this exciting technology later Briefly put, Tela is an agentic AI mesh that operates within the workflows and data environments our customers already use. briefly put tela is an agentic ai mesh that operates within the workflows and data environments our customers already use Its architecture follows a continuous loop: observe, plan, generate, act, and learn. its architecture follows a continuous loop observe plan generate act and learn It is grounded in domain models and industry-specific guardrails that SLB has built. it is grounded in domain models and industry-specific guardrails that slb has built Before I hand it to Trygve to share more details on our platform approach, let's hear from a key customer in the Middle East. before i hand it to trygve to share more details on our platform approach let's hear from a key customer in the middle east

Speaker 25: At the core of ADNOC's subsurface AI strategy is ENERGYai, which brings agentic AI into upstream workflow. Built with technology partners, including SLB, ENERGYai uses digital platforms, including Lumi and Delfi to enable integrated workflows and accelerate deployment at scale. This represents the world's first private cloud deployment, enabling intelligence and integrated workflows across the enterprise. Starting with 42 agentic AI-driven subsurface use cases, spanning from seismic interpretation to reservoir simulation, ADNOC can accelerate reservoir understanding, enhance field development planning, and identify new resource opportunities. For productions and operations, the strategy is driven by AI PSO, delivering more than 25 connected workflows that enable smart, autonomous operations. These capabilities support greater operational efficiency, improved decision-making, and increased performance at scale. The opportunities ahead are significant, and together with technology partners like SLB, we are well on our way to meet our ambitions. At the core of ADNOC's subsurface AI strategy is ENERGYai, which brings agentic AI into upstream workflow. at the core of adnoc's subsurface ai strategy is energyai which brings agentic ai into upstream workflow Built with technology partners, including SLB, ENERGYai uses digital platforms, including Lumi and Delfi to enable integrated workflows and accelerate deployment at scale. built with technology partners including slb energyai uses digital platforms including lumi and delfi to enable integrated workflows and accelerate deployment at scale This represents the world's first private cloud deployment, enabling intelligence and integrated workflows across the enterprise. this represents the world's first private cloud deployment enabling intelligence and integrated workflows across the enterprise Starting with 42 agentic AI-driven subsurface use cases, spanning from seismic interpretation to reservoir simulation, ADNOC can accelerate reservoir understanding, enhance field development planning, and identify new resource opportunities. starting with 42 agentic ai-driven subsurface use cases spanning from seismic interpretation to reservoir simulation adnoc can accelerate reservoir understanding enhance field development planning and identify new resource opportunities For productions and operations, the strategy is driven by AI PSO, delivering more than 25 connected workflows that enable smart, autonomous operations. for productions and operations the strategy is driven by ai pso delivering more than 25 connected workflows that enable smart autonomous operations These capabilities support greater operational efficiency, improved decision-making, and increased performance at scale. these capabilities support greater operational efficiency improved decision-making and increased performance at scale The opportunities ahead are significant, and together with technology partners like SLB, we are well on our way to meet our ambitions. the opportunities ahead are significant and together with technology partners like slb we are well on our way to meet our ambitions

Speaker 1: Congratulations to SLB on 100 years of leadership and innovation. We are proud of our partnership and excited about what the future holds. Congratulations to SLB on 100 years of leadership and innovation. congratulations to slb on 100 years of leadership and innovation We are proud of our partnership and excited about what the future holds. we are proud of our partnership and excited about what the future holds

Speaker 22: Shukran, Ali, and thank you, Rakesh. The SLB's platform approach has been a cornerstone of our digital strategy for over two decades. To start, it's worth grounding what we mean by platforms because the term can be used loosely. Our platform must do two things, provide and make an enterprise trusted data available and accessible And provide an open environment in where that data is consumed by applications, by workflows, and increasingly, by AI. It is the layer that makes everything work together at scale. In our industry, that bar is unusually high. As Rakesh explained, data in our industry is complex, domain-specific, and often business and safety-critical. The workflows span multiple scientific and engineering disciplines. The operating environments are global and frequently constrained by data residency and increasingly, technology sovereignty constraints. A horizontal multipurpose cloud platform does not meet these needs. Shukran, Ali, and thank you, Rakesh. shukran ali and thank you rakesh The SLB's platform approach has been a cornerstone of our digital strategy for over two decades. the slb's platform approach has been a cornerstone of our digital strategy for over two decades To start, it's worth grounding what we mean by platforms because the term can be used loosely. to start it's worth grounding what we mean by platforms because the term can be used loosely Our platform must do two things, provide and make an enterprise trusted data available and accessible And provide an open environment in where that data is consumed by applications, by workflows, and increasingly, by AI. our platform must do two things provide and make an enterprise trusted data available and accessible and provide an open environment in where that data is consumed by applications by workflows and increasingly by ai It is the layer that makes everything work together at scale. it is the layer that makes everything work together at scale In our industry, that bar is unusually high. in our industry that bar is unusually high As Rakesh explained, data in our industry is complex, domain-specific, and often business and safety-critical. as rakesh explained data in our industry is complex domain-specific and often business and safety-critical The workflows span multiple scientific and engineering disciplines. the workflows span multiple scientific and engineering disciplines The operating environments are global and frequently constrained by data residency and increasingly, technology sovereignty constraints. the operating environments are global and frequently constrained by data residency and increasingly technology sovereignty constraints A horizontal multipurpose cloud platform does not meet these needs. a horizontal multipurpose cloud platform does not meet these needs What is required are platforms built for the domain that understand the data, understand the workflows, and can operate at enterprise scale for the most demanding customers. Our customers operate in a world of multiple vendors and proprietary data. We accommodate customers who wish to bring their intellectual property and run it alongside ours in a governed environment. We even partner with many of our customers to co-develop technology. Through open APIs and an extensible application framework, a concept we pioneered 20 years ago with the industry's first open API and plug-in environment, customers and third-party developers can deploy their own technology, their own algorithms, alongside ours in Delfi, Lumi, and Tela. They bring their workflows, we provide the platform. Turning to security, our platforms operate under the tightest standards with data encrypted in transit and at rest, multi-factor authentication, and role-based access control. What is required are platforms built for the domain that understand the data, understand the workflows, and can operate at enterprise scale for the most demanding customers. what is required are platforms built for the domain that understand the data understand the workflows and can operate at enterprise scale for the most demanding customers Our customers operate in a world of multiple vendors and proprietary data. our customers operate in a world of multiple vendors and proprietary data We accommodate customers who wish to bring their intellectual property and run it alongside ours in a governed environment. we accommodate customers who wish to bring their intellectual property and run it alongside ours in a governed environment We even partner with many of our customers to co-develop technology. we even partner with many of our customers to co-develop technology Through open APIs and an extensible application framework, a concept we pioneered 20 years ago with the industry's first open API and plug-in environment, customers and third-party developers can deploy their own technology, their own algorithms, alongside ours in Delfi, Lumi, and Tela. through open apis and an extensible application framework a concept we pioneered 20 years ago with the industry's first open api and plug-in environment customers and third-party developers can deploy their own technology their own algorithms alongside ours in delfi lumi and tela They bring their workflows, we provide the platform. they bring their workflows we provide the platform Turning to security, our platforms operate under the tightest standards with data encrypted in transit and at rest, multi-factor authentication, and role-based access control. turning to security our platforms operate under the tightest standards with data encrypted in transit and at rest multi-factor authentication and role-based access control For an industry that deals in competitive sensitive data and that operates under regulatory oversight, this is not a feature but a prerequisite. There is no doubt we have the data, but one of the structural constraints that has held this industry back is the physical limitations of traditional computing infrastructure. Our reservoir simulation that takes three weeks to run on a workstation can run overnight using elastic cloud resources. A seismic processing job that would require a dedicated data center can be scaled on demand and released when complete. Lumi provides scalable storage and governance for petabytes of operational and subsurface data. Delfi provides on-demand compute for simulation, processing, model training with no ceiling and capacity. The shift from evaluating three development scenarios to evaluating 300 has a dramatic impact on our customers' understanding of development risk, and is only possible when compute is no longer the constraints. For an industry that deals in competitive sensitive data and that operates under regulatory oversight, this is not a feature but a prerequisite. for an industry that deals in competitive sensitive data and that operates under regulatory oversight this is not a feature but a prerequisite There is no doubt we have the data, but one of the structural constraints that has held this industry back is the physical limitations of traditional computing infrastructure. there is no doubt we have the data but one of the structural constraints that has held this industry back is the physical limitations of traditional computing infrastructure Our reservoir simulation that takes three weeks to run on a workstation can run overnight using elastic cloud resources. our reservoir simulation that takes three weeks to run on a workstation can run overnight using elastic cloud resources A seismic processing job that would require a dedicated data center can be scaled on demand and released when complete. a seismic processing job that would require a dedicated data center can be scaled on demand and released when complete Lumi provides scalable storage and governance for petabytes of operational and subsurface data. lumi provides scalable storage and governance for petabytes of operational and subsurface data Delfi provides on-demand compute for simulation, processing, model training with no ceiling and capacity. delfi provides on-demand compute for simulation processing model training with no ceiling and capacity The shift from evaluating three development scenarios to evaluating 300 has a dramatic impact on our customers' understanding of development risk, and is only possible when compute is no longer the constraints. the shift from evaluating three development scenarios to evaluating 300 has a dramatic impact on our customers' understanding of development risk and is only possible when compute is no longer the constraints Our platforms remove that constraints. Rakesh has explained Tela and the domain foundation models within Lumi, but it is worth stating plainly what this means. Every agentic AI deployed in this industry depends on the quality of the models, the quality of the data on which these models are trained, and the quality of the domain science that governs their output. We have all three. Our models are trained on all that we know and allow our customers to enrich them with all that they know. They are grounded in physics, not just pattern recognition. They are deployed within an agentic framework that can act, not just advise. When we describe our digital platforms, we are describing something quite specific. Not a collection of point solutions, not desktop applications moved to the cloud. Our platforms remove that constraints. our platforms remove that constraints Rakesh has explained Tela and the domain foundation models within Lumi, but it is worth stating plainly what this means. rakesh has explained tela and the domain foundation models within lumi but it is worth stating plainly what this means Every agentic AI deployed in this industry depends on the quality of the models, the quality of the data on which these models are trained, and the quality of the domain science that governs their output. every agentic ai deployed in this industry depends on the quality of the models the quality of the data on which these models are trained and the quality of the domain science that governs their output We have all three. we have all three Our models are trained on all that we know and allow our customers to enrich them with all that they know. our models are trained on all that we know and allow our customers to enrich them with all that they know They are grounded in physics, not just pattern recognition. they are grounded in physics not just pattern recognition They are deployed within an agentic framework that can act, not just advise. they are deployed within an agentic framework that can act not just advise When we describe our digital platforms, we are describing something quite specific. when we describe our digital platforms we are describing something quite specific Not a collection of point solutions, not desktop applications moved to the cloud. not a collection of point solutions not desktop applications moved to the cloud An integrated open platform environment underpinned by the industry's deepest data architecture, powered by domain-native AI, and designed to serve the full life cycle of an upstream asset. There is no other platform in the energy industry that offers this combination of workflow depth, data breadth, domain intelligence, extensibility, and enterprise-grade infrastructure. That is the position we have created, and it is the position we will extend. The final aspect is our partner ecosystem. Let me dive deeper into that. I should be clear that we did not build all of this alone. We have more than 40 strategic partners are contributing capability across our platform. I will talk about them in a moment, but the ecosystem extends well beyond our strategic partnerships. More than 175 commercial plug-ins are available on our platforms. An integrated open platform environment underpinned by the industry's deepest data architecture, powered by domain-native AI, and designed to serve the full life cycle of an upstream asset. an integrated open platform environment underpinned by the industry's deepest data architecture powered by domain-native ai and designed to serve the full life cycle of an upstream asset There is no other platform in the energy industry that offers this combination of workflow depth, data breadth, domain intelligence, extensibility, and enterprise-grade infrastructure. there is no other platform in the energy industry that offers this combination of workflow depth data breadth domain intelligence extensibility and enterprise-grade infrastructure That is the position we have created, and it is the position we will extend. that is the position we have created and it is the position we will extend The final aspect is our partner ecosystem. the final aspect is our partner ecosystem Let me dive deeper into that. let me dive deeper into that I should be clear that we did not build all of this alone. i should be clear that we did not build all of this alone We have more than 40 strategic partners are contributing capability across our platform. we have more than 40 strategic partners are contributing capability across our platform I will talk about them in a moment, but the ecosystem extends well beyond our strategic partnerships. i will talk about them in a moment but the ecosystem extends well beyond our strategic partnerships More than 175 commercial plug-ins are available on our platforms. more than 175 commercial plug-ins are available on our platforms Developed by third parties who are built on our open APIs and frameworks, and more than 110 third-party applications are hosted on the platform, accessible to our customers alongside our own. This matters for two reasons. First, it is evident that openness is a reality, not just a philosophy. Developers and technology companies are investing their own money and resources building on our platforms because the customer reach, the data environment, the commercial opportunity justify that investment. That is the hallmark of a genuine platform ecosystem. Second, it deepens the moat. Every third-party application, every partner integration increases the value of the platform. The ecosystem compounds our own investments and makes the platform more valuable in ways we do not have to build or fund ourselves. Developed by third parties who are built on our open APIs and frameworks, and more than 110 third-party applications are hosted on the platform, accessible to our customers alongside our own. developed by third parties who are built on our open apis and frameworks and more than 110 third-party applications are hosted on the platform accessible to our customers alongside our own This matters for two reasons. this matters for two reasons First, it is evident that openness is a reality, not just a philosophy. first it is evident that openness is a reality not just a philosophy Developers and technology companies are investing their own money and resources building on our platforms because the customer reach, the data environment, the commercial opportunity justify that investment. developers and technology companies are investing their own money and resources building on our platforms because the customer reach the data environment the commercial opportunity justify that investment That is the hallmark of a genuine platform ecosystem. that is the hallmark of a genuine platform ecosystem Second, it deepens the moat. second it deepens the moat Every third-party application, every partner integration increases the value of the platform. every third-party application every partner integration increases the value of the platform The ecosystem compounds our own investments and makes the platform more valuable in ways we do not have to build or fund ourselves. the ecosystem compounds our own investments and makes the platform more valuable in ways we do not have to build or fund ourselves In addition to the other vendors who have brought their IP to our platform, our strategic partner ecosystem above that network is structured in six layers, each serving a distinct function in the platform. We have foundational partnerships with AWS, Google, and Microsoft, the hyperscalers. They are drawn to us as the market leader in the domain, and we are drawn to them for their modern cloud infrastructure on which Delfi and Lumi run. Multi-cloud support is not a convenience but a requirement. Our customers operate all over the world, many with strict data residency constraints. Being cloud agnostic means we can deploy wherever the customer needs us. We can also deploy on the edge using our Agora edge AI platform. Agora addresses the real-time demands of remote environments where connectivity, latency, cybersecurity, and operational continuity affect performance. In addition to the other vendors who have brought their IP to our platform, our strategic partner ecosystem above that network is structured in six layers, each serving a distinct function in the platform. in addition to the other vendors who have brought their ip to our platform our strategic partner ecosystem above that network is structured in six layers each serving a distinct function in the platform We have foundational partnerships with AWS, Google, and Microsoft, the hyperscalers. we have foundational partnerships with aws google and microsoft the hyperscalers They are drawn to us as the market leader in the domain, and we are drawn to them for their modern cloud infrastructure on which Delfi and Lumi run. they are drawn to us as the market leader in the domain and we are drawn to them for their modern cloud infrastructure on which delfi and lumi run Multi-cloud support is not a convenience but a requirement. multi-cloud support is not a convenience but a requirement Our customers operate all over the world, many with strict data residency constraints. our customers operate all over the world many with strict data residency constraints Being cloud agnostic means we can deploy wherever the customer needs us. being cloud agnostic means we can deploy wherever the customer needs us We can also deploy on the edge using our Agora edge AI platform. we can also deploy on the edge using our agora edge ai platform Agora addresses the real-time demands of remote environments where connectivity, latency, cybersecurity, and operational continuity affect performance. agora addresses the real-time demands of remote environments where connectivity latency cybersecurity and operational continuity affect performance I won't expand upon the other layers in this. The point is not the number of logos. We could have added many more. It is the architecture. Every layer is deliberate. Every partner is best in breed in their domain, and together they create a platform that is comprehensive without being closed. Let's hear from some of these valued partners. I won't expand upon the other layers in this. i won't expand upon the other layers in this The point is not the number of logos. the point is not the number of logos We could have added many more. we could have added many more It is the architecture. it is the architecture Every layer is deliberate. every layer is deliberate Every partner is best in breed in their domain, and together they create a platform that is comprehensive without being closed. every partner is best in breed in their domain and together they create a platform that is comprehensive without being closed Let's hear from some of these valued partners. let's hear from some of these valued partners

Speaker 30: Microsoft and SLB have worked together for decades, evolving alongside some of the biggest shifts the energy industry has seen. That collaboration sets the foundation for how we work together, combining deep domain expertise with powerful platforms. Microsoft and SLB have worked together for decades, evolving alongside some of the biggest shifts the energy industry has seen. microsoft and slb have worked together for decades evolving alongside some of the biggest shifts the energy industry has seen That collaboration sets the foundation for how we work together, combining deep domain expertise with powerful platforms. that collaboration sets the foundation for how we work together combining deep domain expertise with powerful platforms

Speaker 29: As SLB enters its second century of technical leadership, Google Cloud is ready to anchor your vision with our own pioneering investments in advanced energy. As SLB enters its second century of technical leadership, Google Cloud is ready to anchor your vision with our own pioneering investments in advanced energy. as slb enters its second century of technical leadership google cloud is ready to anchor your vision with our own pioneering investments in advanced energy

Speaker 26: Together, SLB and AWS are building the digital backbone so our joint customers can perform at an AI-accelerated level. Together, SLB and AWS are building the digital backbone so our joint customers can perform at an AI-accelerated level. together slb and aws are building the digital backbone so our joint customers can perform at an ai-accelerated level

Speaker 24: We are entering a new industrial era powered by AI, and energy sits at the center of it. We focus very strongly on strategic partnerships like the one with SLB. SLB brings digital and domain expertise across subsurface, subsea, and topside production systems. We are entering a new industrial era powered by AI, and energy sits at the center of it. we are entering a new industrial era powered by ai and energy sits at the center of it We focus very strongly on strategic partnerships like the one with SLB. we focus very strongly on strategic partnerships like the one with slb SLB brings digital and domain expertise across subsurface, subsea, and topside production systems. slb brings digital and domain expertise across subsurface subsea and topside production systems

Speaker 27: 80% faster in competition cycles, earning success rates that are changing the economics of natural assets. 80% faster in competition cycles, earning success rates that are changing the economics of natural assets. 80% faster in competition cycles earning success rates that are changing the economics of natural assets

Speaker 24: Together, we deliver grounded real-time insights that drive action. One joint customer of ours increased production by 100,000 barrels and also saved $4.3 million in operating expenses. Together, we deliver grounded real-time insights that drive action. together we deliver grounded real-time insights that drive action One joint customer of ours increased production by 100,000 barrels and also saved $4.3 million in operating expenses. one joint customer of ours increased production by 100,000 barrels and also saved $4.3 million in operating expenses Together, we are creating a foundation that helps SLB move faster, operate smarter, and deliver more value to customers around the world. Together, we are creating a foundation that helps SLB move faster, operate smarter, and deliver more value to customers around the world. together we are creating a foundation that helps slb move faster operate smarter and deliver more value to customers around the world

Speaker 22: Quite some heavy hitters that gave their video statements there. I want to emphasize on something that comes from these videos, and that is one of the most significant barriers to entry in our industry, trust. Our customers trust us with their most competitively sensitive data. Seismic surveys that cost hundreds of millions of dollars to acquire. Reservoir models that underpin the multi-billion development decisions and real-time operational data from producing assets. This is data that governments regulate, that boards scrutinize, and that our customers' competitors would love to see. We deliver our trusted platforms across more than 80 countries, essentially everywhere that oil and gas is found. Each with its own regulatory framework, its own data and technology requirements, and in many cases, its own constraints on which cloud infrastructure is permissible or even available. Quite some heavy hitters that gave their video statements there. quite some heavy hitters that gave their video statements there I want to emphasize on something that comes from these videos, and that is one of the most significant barriers to entry in our industry, trust. i want to emphasize on something that comes from these videos and that is one of the most significant barriers to entry in our industry trust Our customers trust us with their most competitively sensitive data. our customers trust us with their most competitively sensitive data Seismic surveys that cost hundreds of millions of dollars to acquire. seismic surveys that cost hundreds of millions of dollars to acquire Reservoir models that underpin the multi-billion development decisions and real-time operational data from producing assets. reservoir models that underpin the multi-billion development decisions and real-time operational data from producing assets This is data that governments regulate, that boards scrutinize, and that our customers' competitors would love to see. this is data that governments regulate that boards scrutinize and that our customers' competitors would love to see We deliver our trusted platforms across more than 80 countries, essentially everywhere that oil and gas is found. we deliver our trusted platforms across more than 80 countries essentially everywhere that oil and gas is found Each with its own regulatory framework, its own data and technology requirements, and in many cases, its own constraints on which cloud infrastructure is permissible or even available. each with its own regulatory framework its own data and technology requirements and in many cases its own constraints on which cloud infrastructure is permissible or even available Solving for all these constraints at scale requires multi-cloud deployment capabilities, on-premise options, and a deep operational understanding of the legal and political landscape in every market we serve. A national oil company in the Middle East has fundamentally different requirements from an independent operating in the U.S. or a multinational operating in deep water Brazil. We serve all of them, whatever their infrastructure constraints. In addition to sovereignty, reliability reinforces our customers' trust in SLB. We are well in excess of 99.5% uptime. In many cases, we continue delivering our services even when the hyperscaler goes down. It is possible precisely because we operate across multiple cloud providers. If one goes down, we move over to another. Our customers' workflows do not stop because a data center in a single region has an outage. Solving for all these constraints at scale requires multi-cloud deployment capabilities, on-premise options, and a deep operational understanding of the legal and political landscape in every market we serve. solving for all these constraints at scale requires multi-cloud deployment capabilities on-premise options and a deep operational understanding of the legal and political landscape in every market we serve A national oil company in the Middle East has fundamentally different requirements from an independent operating in the U.S. or a multinational operating in deep water Brazil. a national oil company in the middle east has fundamentally different requirements from an independent operating in the u.s or a multinational operating in deep water brazil We serve all of them, whatever their infrastructure constraints. we serve all of them whatever their infrastructure constraints In addition to sovereignty, reliability reinforces our customers' trust in SLB. in addition to sovereignty reliability reinforces our customers' trust in slb We are well in excess of 99.5% uptime. we are well in excess of 99.5% uptime In many cases, we continue delivering our services even when the hyperscaler goes down. in many cases we continue delivering our services even when the hyperscaler goes down It is possible precisely because we operate across multiple cloud providers. it is possible precisely because we operate across multiple cloud providers If one goes down, we move over to another. if one goes down we move over to another Our customers' workflows do not stop because a data center in a single region has an outage. our customers' workflows do not stop because a data center in a single region has an outage For an operator running real-time production surveillance or time-critical drilling operations, that resilience is a condition of adoption. If trust is the foundation, scale is the outcome. A scale we have achieved thanks to more than $3 billion of R&D spend since 2016 and 390 digital U.S. patents granted in the last five years. That scale of what we have built is worth dwelling on for a moment, because these numbers are not projections, they are the current state of the business. At the center of this slide, more than 90% of global production is simulated or modeled using at least one of our digital solutions. I'll let that sink in for a moment. That is not a market share statistics, but a measure of how deeply embedded our technology is in the decisions that Rakesh talked about that govern the hydrocarbon output of the world. For an operator running real-time production surveillance or time-critical drilling operations, that resilience is a condition of adoption. for an operator running real-time production surveillance or time-critical drilling operations that resilience is a condition of adoption If trust is the foundation, scale is the outcome. if trust is the foundation scale is the outcome A scale we have achieved thanks to more than $3 billion of R&D spend since 2016 and 390 digital U.S. patents granted in the last five years. a scale we have achieved thanks to more than $3 billion of r&d spend since 2016 and 390 digital u.s patents granted in the last five years That scale of what we have built is worth dwelling on for a moment, because these numbers are not projections, they are the current state of the business. that scale of what we have built is worth dwelling on for a moment because these numbers are not projections they are the current state of the business At the center of this slide, more than 90% of global production is simulated or modeled using at least one of our digital solutions. at the center of this slide more than 90% of global production is simulated or modeled using at least one of our digital solutions I'll let that sink in for a moment. i'll let that sink in for a moment That is not a market share statistics, but a measure of how deeply embedded our technology is in the decisions that Rakesh talked about that govern the hydrocarbon output of the world. that is not a market share statistics but a measure of how deeply embedded our technology is in the decisions that rakesh talked about that govern the hydrocarbon output of the world Around it, the operational footprint. More than half a million feet drilled each quarter using SLB automation technology. Over 2 billion API calls across the platform in 2025, a proxy for the volume of machine-to-machine interaction, executing continuously across our infrastructure. Over 45 million CPU hours in Q1 of this year alone and growing as customers are unlocking the simulation processing and AI workloads we discussed earlier. Supported by over 2,600 petrotechnical experts, the largest team in the industry. The position is built. The question is now how fast and how far we can grow from it. Well, let me hand back to Rakesh to describe the market opportunity. Around it, the operational footprint. around it the operational footprint More than half a million feet drilled each quarter using SLB automation technology. more than half a million feet drilled each quarter using slb automation technology Over 2 billion API calls across the platform in 2025, a proxy for the volume of machine-to-machine interaction, executing continuously across our infrastructure. over 2 billion api calls across the platform in 2025 a proxy for the volume of machine-to-machine interaction executing continuously across our infrastructure Over 45 million CPU hours in Q1 of this year alone and growing as customers are unlocking the simulation processing and AI workloads we discussed earlier. over 45 million cpu hours in q1 of this year alone and growing as customers are unlocking the simulation processing and ai workloads we discussed earlier Supported by over 2,600 petrotechnical experts, the largest team in the industry. supported by over 2,600 petrotechnical experts the largest team in the industry The position is built. the position is built The question is now how fast and how far we can grow from it. the question is now how fast and how far we can grow from it Well, let me hand back to Rakesh to describe the market opportunity. well let me hand back to rakesh to describe the market opportunity

Speaker 15: Thank you, Trygve. I would now like to define and quantify the market we play in, ladies and gentlemen. This chart from Gartner shows the digital spend as a percentage of the total expenditure across major industries. Oil and gas digital spend, 4%-5%, considerably less than manufacturing and natural resources that you might expect to closely correlate. The point is simple. Oil and gas is one of the most data-intensive, technically complex, and capital-heavy industries on Earth. Yet it spends proportionally less on digital technology than almost any comparable sector. However, this is not a market where we are merely fighting for a share of a fixed pie. The pie itself is growing, and it is growing because the industry is underinvesting relative to its complexity, and the technology to close that gap now exists. Thank you, Trygve. thank you trygve I would now like to define and quantify the market we play in, ladies and gentlemen. i would now like to define and quantify the market we play in ladies and gentlemen This chart from Gartner shows the digital spend as a percentage of the total expenditure across major industries. this chart from gartner shows the digital spend as a percentage of the total expenditure across major industries Oil and gas digital spend, 4%-5%, considerably less than manufacturing and natural resources that you might expect to closely correlate. oil and gas digital spend 4%-5% considerably less than manufacturing and natural resources that you might expect to closely correlate The point is simple. the point is simple Oil and gas is one of the most data-intensive, technically complex, and capital-heavy industries on Earth. oil and gas is one of the most data-intensive technically complex and capital-heavy industries on earth Yet it spends proportionally less on digital technology than almost any comparable sector. yet it spends proportionally less on digital technology than almost any comparable sector However, this is not a market where we are merely fighting for a share of a fixed pie. however this is not a market where we are merely fighting for a share of a fixed pie The pie itself is growing, and it is growing because the industry is underinvesting relative to its complexity, and the technology to close that gap now exists. the pie itself is growing and it is growing because the industry is underinvesting relative to its complexity and the technology to close that gap now exists Less than half of that investment supports the technical workloads that we've been talking about this morning. That is where we play and where emerging tech disruptions will bring significant value to our industry. According to Rystad Energy, this market in 2025 represented about $25 billion. Looking at the breakdown of this digital TAM, customers are allocating digital spend across planning and development, operations, and their enterprise digital infrastructure. Furthermore, the capabilities I've been talking about have only recently matured to the point where they will become compelling. For us, this means the total addressable market has significant room to expand. Another way to look at this market is through the lens of the main player in this TAM. On the top right here are the traditional oilfield services and equipment competitors. They compete with us in domain-specific software, particularly in planning and drilling. Less than half of that investment supports the technical workloads that we've been talking about this morning. less than half of that investment supports the technical workloads that we've been talking about this morning That is where we play and where emerging tech disruptions will bring significant value to our industry. that is where we play and where emerging tech disruptions will bring significant value to our industry According to Rystad Energy, this market in 2025 represented about $25 billion. according to rystad energy this market in 2025 represented about $25 billion Looking at the breakdown of this digital TAM, customers are allocating digital spend across planning and development, operations, and their enterprise digital infrastructure. looking at the breakdown of this digital tam customers are allocating digital spend across planning and development operations and their enterprise digital infrastructure Furthermore, the capabilities I've been talking about have only recently matured to the point where they will become compelling. furthermore the capabilities i've been talking about have only recently matured to the point where they will become compelling For us, this means the total addressable market has significant room to expand. for us this means the total addressable market has significant room to expand Another way to look at this market is through the lens of the main player in this TAM. another way to look at this market is through the lens of the main player in this tam On the top right here are the traditional oilfield services and equipment competitors. on the top right here are the traditional oilfield services and equipment competitors They compete with us in domain-specific software, particularly in planning and drilling. they compete with us in domain-specific software particularly in planning and drilling We are unmatched in our investment in platform modernization and in artificial intelligence. Next, the industrial technology companies. These are very credible players in operational technology, particularly in surface automation, process control, and equipment monitoring. They bring strong capabilities in the industrial IoT and facilities layer. We compete with them in operations. They lack subsurface domain expertise. The enterprise technology companies, which serve the industry's broader IT needs, networking, databases, communications infrastructure, et cetera. They operate horizontally across many industries, but without domain specialization. The system integrators. These firms provide implementation services, custom development, and data migration. They compete with us in services around the data, but they do not own platforms, domain science, nor proprietary AI models. We have the hyperscalers and horizontal platform providers who bring cloud infrastructure, compute, and data storage. We are unmatched in our investment in platform modernization and in artificial intelligence. we are unmatched in our investment in platform modernization and in artificial intelligence Next, the industrial technology companies. next the industrial technology companies These are very credible players in operational technology, particularly in surface automation, process control, and equipment monitoring. these are very credible players in operational technology particularly in surface automation process control and equipment monitoring They bring strong capabilities in the industrial IoT and facilities layer. they bring strong capabilities in the industrial iot and facilities layer We compete with them in operations. we compete with them in operations They lack subsurface domain expertise. they lack subsurface domain expertise The enterprise technology companies, which serve the industry's broader IT needs, networking, databases, communications infrastructure, et cetera. the enterprise technology companies which serve the industry's broader it needs networking databases communications infrastructure et cetera They operate horizontally across many industries, but without domain specialization. they operate horizontally across many industries but without domain specialization The system integrators. the system integrators These firms provide implementation services, custom development, and data migration. these firms provide implementation services custom development and data migration They compete with us in services around the data, but they do not own platforms, domain science, nor proprietary AI models. they compete with us in services around the data but they do not own platforms domain science nor proprietary ai models We have the hyperscalers and horizontal platform providers who bring cloud infrastructure, compute, and data storage. we have the hyperscalers and horizontal platform providers who bring cloud infrastructure compute and data storage They are essential to the ecosystem, but they are not competitors in the domain software. As we've described, many are already partners providing the infrastructure on which our platforms run. We are the only company equipped to address a majority of this market. Rather than competing with the hyperscalers and system integrators, we have made them a part of our architecture. Their infrastructure powers our platforms. Their compute is used to fuel our AI models, and their services assure rapid market adoption of our platforms. In other words, we convert potential competitors into distribution and capability partners. On the other side, our open platform architecture means the technology of others can integrate into our environment. We do not require the customers to choose between us and these companies. We provide the platforms on which they coexist. They are essential to the ecosystem, but they are not competitors in the domain software. they are essential to the ecosystem but they are not competitors in the domain software As we've described, many are already partners providing the infrastructure on which our platforms run. as we've described many are already partners providing the infrastructure on which our platforms run We are the only company equipped to address a majority of this market. we are the only company equipped to address a majority of this market Rather than competing with the hyperscalers and system integrators, we have made them a part of our architecture. rather than competing with the hyperscalers and system integrators we have made them a part of our architecture Their infrastructure powers our platforms. their infrastructure powers our platforms Their compute is used to fuel our AI models, and their services assure rapid market adoption of our platforms. their compute is used to fuel our ai models and their services assure rapid market adoption of our platforms In other words, we convert potential competitors into distribution and capability partners. in other words we convert potential competitors into distribution and capability partners On the other side, our open platform architecture means the technology of others can integrate into our environment. on the other side our open platform architecture means the technology of others can integrate into our environment We do not require the customers to choose between us and these companies. we do not require the customers to choose between us and these companies We provide the platforms on which they coexist. we provide the platforms on which they coexist Other companies occupy a segment, we occupy the entire space, more than two-thirds of the market. Our openness turns these companies into participants in our ecosystem rather than obstacles to our growth. I now want to spend a few minutes talking about how this market is expected to evolve. By 2030, the expectation is that another $10 billion in annual spend will be added as digital spend becomes further decoupled from the overall industry CapEx and OpEx. This growth is driven by our customers' ambition to secure greater value from digital, especially in operations where significant value is expected. You will hear more about this in the next section. The most important number is the one on the top right. With accelerated AI adoption, the total market could reach as much as $50 billion by 2030. This reflects what happens when AI fundamentally changes the nature of digital work. Other companies occupy a segment, we occupy the entire space, more than two-thirds of the market. other companies occupy a segment we occupy the entire space more than two-thirds of the market Our openness turns these companies into participants in our ecosystem rather than obstacles to our growth. our openness turns these companies into participants in our ecosystem rather than obstacles to our growth I now want to spend a few minutes talking about how this market is expected to evolve. i now want to spend a few minutes talking about how this market is expected to evolve By 2030, the expectation is that another $10 billion in annual spend will be added as digital spend becomes further decoupled from the overall industry CapEx and OpEx. by 2030 the expectation is that another $10 billion in annual spend will be added as digital spend becomes further decoupled from the overall industry capex and opex This growth is driven by our customers' ambition to secure greater value from digital, especially in operations where significant value is expected. this growth is driven by our customers' ambition to secure greater value from digital especially in operations where significant value is expected You will hear more about this in the next section. you will hear more about this in the next section The most important number is the one on the top right. the most important number is the one on the top right With accelerated AI adoption, the total market could reach as much as $50 billion by 2030. with accelerated ai adoption the total market could reach as much as $50 billion by 2030 This reflects what happens when AI fundamentally changes the nature of digital work. this reflects what happens when ai fundamentally changes the nature of digital work When interpretations become exponentially faster, customers do more of them. When simulations are no longer constrained by hardware limitations, teams run hundreds of scenarios instead of just a few. When agentic workflows automate routine surveillance across thousands of wells, digital spend expands. It does not just make existing work more efficient, it unlocks possibilities that were previously uneconomic. For us, this is the most important dynamic. We are not competing for a larger share of a static opportunity. The opportunity itself is accelerating, driven by the same AI capabilities that we are building into our platforms. That, ladies and gentlemen, is our digital advantage. With that, let's now zoom in onto two parts of this market that are growing the fastest, digital operations and AI. These will unlock the possible doubling of this market. When interpretations become exponentially faster, customers do more of them. when interpretations become exponentially faster customers do more of them When simulations are no longer constrained by hardware limitations, teams run hundreds of scenarios instead of just a few. when simulations are no longer constrained by hardware limitations teams run hundreds of scenarios instead of just a few When agentic workflows automate routine surveillance across thousands of wells, digital spend expands. when agentic workflows automate routine surveillance across thousands of wells digital spend expands It does not just make existing work more efficient, it unlocks possibilities that were previously uneconomic. it does not just make existing work more efficient it unlocks possibilities that were previously uneconomic For us, this is the most important dynamic. for us this is the most important dynamic We are not competing for a larger share of a static opportunity. we are not competing for a larger share of a static opportunity The opportunity itself is accelerating, driven by the same AI capabilities that we are building into our platforms. the opportunity itself is accelerating driven by the same ai capabilities that we are building into our platforms That, ladies and gentlemen, is our digital advantage. that ladies and gentlemen is our digital advantage With that, let's now zoom in onto two parts of this market that are growing the fastest, digital operations and AI. with that let's now zoom in onto two parts of this market that are growing the fastest digital operations and ai These will unlock the possible doubling of this market. these will unlock the possible doubling of this market You're about to hear from Cecilia and Shashi, who will share how our digital capabilities are transforming operations and how AI is expected to disrupt our industry. Before Cecilia takes the stage, let's hear from a few more of our customers. Thank you. You're about to hear from Cecilia and Shashi, who will share how our digital capabilities are transforming operations and how AI is expected to disrupt our industry. you're about to hear from cecilia and shashi who will share how our digital capabilities are transforming operations and how ai is expected to disrupt our industry Before Cecilia takes the stage, let's hear from a few more of our customers. before cecilia takes the stage let's hear from a few more of our customers Thank you. thank you

Speaker 24: Our digital collaboration with SLB brings together deep domain expertise, scale, and capability to address the specific challenges across the subsurface, well construction, and production. Our digital collaboration with SLB brings together deep domain expertise, scale, and capability to address the specific challenges across the subsurface, well construction, and production. our digital collaboration with slb brings together deep domain expertise scale and capability to address the specific challenges across the subsurface well construction and production Through this collaboration, we have strengthened our ability to understand subsurface complexity, optimize drilling, and make better decisions faster. Analysis that previously took months can now be completed in weeks or even days. Through this collaboration, we have strengthened our ability to understand subsurface complexity, optimize drilling, and make better decisions faster. through this collaboration we have strengthened our ability to understand subsurface complexity optimize drilling and make better decisions faster Analysis that previously took months can now be completed in weeks or even days. analysis that previously took months can now be completed in weeks or even days

Speaker 29: With SLB solutions, particularly OptiFlow, OptiSite, and Agora, YTS will comprehensively optimize production and the facilities, improving performance, efficiency, and operational integrity. With SLB solutions, particularly OptiFlow, OptiSite, and Agora, YTS will comprehensively optimize production and the facilities, improving performance, efficiency, and operational integrity. with slb solutions particularly optiflow optisite and agora yts will comprehensively optimize production and the facilities improving performance efficiency and operational integrity

Speaker 24: We are now building on this strong foundation by expanding our collaboration into production, including the pilot of AI-driven tools for real-time optimization. We are now building on this strong foundation by expanding our collaboration into production, including the pilot of AI-driven tools for real-time optimization. we are now building on this strong foundation by expanding our collaboration into production including the pilot of ai-driven tools for real-time optimization We deploy SLB technology on the majority of our wells through artificial lift data transformation, through chemical data transformation. While that process has often been manual in how we optimize, we're starting to breach the world of automation and machine learning. We deploy SLB technology on the majority of our wells through artificial lift data transformation, through chemical data transformation. we deploy slb technology on the majority of our wells through artificial lift data transformation through chemical data transformation While that process has often been manual in how we optimize, we're starting to breach the world of automation and machine learning. while that process has often been manual in how we optimize we're starting to breach the world of automation and machine learning We implemented the SLB Agora solution as a pilot approximately six months or so ago, and we saw an immediate 15%-20% uplift relative to how we were doing it. We implemented the SLB Agora solution as a pilot approximately six months or so ago, and we saw an immediate 15%-20% uplift relative to how we were doing it. we implemented the slb agora solution as a pilot approximately six months or so ago and we saw an immediate 15%-20% uplift relative to how we were doing it Delfi has become the platform on which we bring new technology into our subsurface workflows. We keep adding these features to our main process, which means we are able to work together more easily, grow as needed, and deliver more value across the company. Delfi has become the platform on which we bring new technology into our subsurface workflows. delfi has become the platform on which we bring new technology into our subsurface workflows We keep adding these features to our main process, which means we are able to work together more easily, grow as needed, and deliver more value across the company. we keep adding these features to our main process which means we are able to work together more easily grow as needed and deliver more value across the company

Speaker 3: Thank you, Rakesh. I'm Cecilia Prieto, what I'm going to do today is to take you to the physical world, where digital meets operations and delivers results. Our industry is very clear about where we're going. Autonomous operations. That's the destination. The challenge isn't the feasibility. We've already proven that autonomy works. The question is, how do we scale? This can only happen when we are applying digital in every operation. In the next few minutes, I'll tell you how digital has a material impact on our customers' production and lifting costs, and why SLB is best positioned to truly transform the way it is done today. To understand what we can offer and how fast we're scaling, let's take this story from the beginning. We have a vast footprint of services and equipment in the field delivered by our reservoir performance, well construction, and production system divisions. Thank you, Rakesh. thank you rakesh I'm Cecilia Prieto, what I'm going to do today is to take you to the physical world, where digital meets operations and delivers results. i'm cecilia prieto what i'm going to do today is to take you to the physical world where digital meets operations and delivers results Our industry is very clear about where we're going. our industry is very clear about where we're going Autonomous operations. autonomous operations That's the destination. that's the destination The challenge isn't the feasibility. the challenge isn't the feasibility We've already proven that autonomy works. we've already proven that autonomy works The question is, how do we scale? the question is how do we scale This can only happen when we are applying digital in every operation. this can only happen when we are applying digital in every operation In the next few minutes, I'll tell you how digital has a material impact on our customers' production and lifting costs, and why SLB is best positioned to truly transform the way it is done today. in the next few minutes i'll tell you how digital has a material impact on our customers' production and lifting costs and why slb is best positioned to truly transform the way it is done today To understand what we can offer and how fast we're scaling, let's take this story from the beginning. to understand what we can offer and how fast we're scaling let's take this story from the beginning We have a vast footprint of services and equipment in the field delivered by our reservoir performance, well construction, and production system divisions. we have a vast footprint of services and equipment in the field delivered by our reservoir performance well construction and production system divisions This is our sandbox. Our first step is to connect this footprint. That's how we collect data and enable surveillance and control. Our customers pay for this value. Here's just one of many examples. Today, 35% of our electrical submersible pumps are connected and monitored. By 2030, we aim to reach 60%. The next tier is intelligent solutions and services. This is where operational data is turned into actionable insights. Another example, today, about 14% of our formation evaluation operations run with a digital insight add-on. By 2030, our ambition is to drive 60% of adoption amongst our customers. The final destination, autonomy. It is not a dream. It is happening today. 3% of the footage we drill is done autonomously. By 2030, we aim to reach 25%. This is the most advanced form of digital operations and where the industry will unlock the biggest value. Here's the reality. This is our sandbox. this is our sandbox Our first step is to connect this footprint. our first step is to connect this footprint That's how we collect data and enable surveillance and control. that's how we collect data and enable surveillance and control Our customers pay for this value. our customers pay for this value Here's just one of many examples. here's just one of many examples Today, 35% of our electrical submersible pumps are connected and monitored. today 35% of our electrical submersible pumps are connected and monitored By 2030, we aim to reach 60%. by 2030 we aim to reach 60% The next tier is intelligent solutions and services. the next tier is intelligent solutions and services This is where operational data is turned into actionable insights. this is where operational data is turned into actionable insights Another example, today, about 14% of our formation evaluation operations run with a digital insight add-on. another example today about 14% of our formation evaluation operations run with a digital insight add-on By 2030, our ambition is to drive 60% of adoption amongst our customers. by 2030 our ambition is to drive 60% of adoption amongst our customers The final destination, autonomy. the final destination autonomy It is not a dream. it is not a dream It is happening today. 3% of the footage we drill is done autonomously. it is happening today 3% of the footage we drill is done autonomously By 2030, we aim to reach 25%. by 2030 we aim to reach 25% This is the most advanced form of digital operations and where the industry will unlock the biggest value. this is the most advanced form of digital operations and where the industry will unlock the biggest value Here's the reality. here's the reality Drilling a well is extremely challenging. The wells we drill keep getting longer, and our reservoir targets are miles and miles away from the wellhead, with lots of unknown on the way. Unknown rock properties, unknown pressure levels, unknown fractures, porosities, and so much more. Every day, something goes wrong. The industry wastes about $4 billion every year to remediate high-impact events. It can take a few days or even a few weeks to regain control and resume operations. Complexity is multiplied because drilling involves several service companies and rig contractors spanning many individual workflows. Two decades ago, we began digitalizing drilling by collecting and interpreting data in remote operations centers where SLB and our customers work side by side. We needed less personnel at rig sites, preserved key expertise in those centers. Until recently, manual lab measurements and Excel files were still the norm. Drilling a well is extremely challenging. drilling a well is extremely challenging The wells we drill keep getting longer, and our reservoir targets are miles and miles away from the wellhead, with lots of unknown on the way. the wells we drill keep getting longer and our reservoir targets are miles and miles away from the wellhead with lots of unknown on the way Unknown rock properties, unknown pressure levels, unknown fractures, porosities, and so much more. unknown rock properties unknown pressure levels unknown fractures porosities and so much more Every day, something goes wrong. every day something goes wrong The industry wastes about $4 billion every year to remediate high-impact events. the industry wastes about $4 billion every year to remediate high-impact events It can take a few days or even a few weeks to regain control and resume operations. it can take a few days or even a few weeks to regain control and resume operations Complexity is multiplied because drilling involves several service companies and rig contractors spanning many individual workflows. complexity is multiplied because drilling involves several service companies and rig contractors spanning many individual workflows Two decades ago, we began digitalizing drilling by collecting and interpreting data in remote operations centers where SLB and our customers work side by side. two decades ago we began digitalizing drilling by collecting and interpreting data in remote operations centers where slb and our customers work side by side We needed less personnel at rig sites, preserved key expertise in those centers. we needed less personnel at rig sites preserved key expertise in those centers Until recently, manual lab measurements and Excel files were still the norm. until recently manual lab measurements and excel files were still the norm Directional drillers, subsurface experts, and fluid experts were all each receiving more data to interpret and act on. It was a step forward, but they were still working in silos. More integration was needed. That is exactly what we did. We integrated the data and workflows into what we call drilling insights. They provide intelligent recommendations in a standalone workflow or across multiple ones, and this is where we generate 80% of our digital drilling revenue today, on top of SLB drilling services or as a generic application. Here comes the big finale. When we combine drilling insights with bottom hole and surface automation, drilling autonomy becomes a reality. The most optimal decisions are recommended and executed in real time by the system without slowing drilling down. Many decisions can be taken and executed simultaneously. This is simply not humanly possible. Directional drillers, subsurface experts, and fluid experts were all each receiving more data to interpret and act on. directional drillers subsurface experts and fluid experts were all each receiving more data to interpret and act on It was a step forward, but they were still working in silos. it was a step forward but they were still working in silos More integration was needed. more integration was needed That is exactly what we did. that is exactly what we did We integrated the data and workflows into what we call drilling insights. we integrated the data and workflows into what we call drilling insights They provide intelligent recommendations in a standalone workflow or across multiple ones, and this is where we generate 80% of our digital drilling revenue today, on top of SLB drilling services or as a generic application. they provide intelligent recommendations in a standalone workflow or across multiple ones and this is where we generate 80% of our digital drilling revenue today on top of slb drilling services or as a generic application Here comes the big finale. here comes the big finale When we combine drilling insights with bottom hole and surface automation, drilling autonomy becomes a reality. when we combine drilling insights with bottom hole and surface automation drilling autonomy becomes a reality The most optimal decisions are recommended and executed in real time by the system without slowing drilling down. the most optimal decisions are recommended and executed in real time by the system without slowing drilling down Many decisions can be taken and executed simultaneously. many decisions can be taken and executed simultaneously This is simply not humanly possible. this is simply not humanly possible Drilling autonomy is how we drill wells faster and better, always placing them in the production sweet spot. It's how we improve drilling efficiency by 25%-40% and help our customers produce more and reduce lifting costs. Let me tell you about a real example. In Libya, we have been working with Sirte, a subsidiary of the National Oil Corporation. To accelerate well development, autonomous drilling was the answer. Today, Sirte produces around 110,000 barrels of oil per day with ambition to increase this further and fast. This is critical to the country's national production and economical development. We deployed DrillOps automation with all the drilling insights, orchestration, autonomous well placement, and bottom hole automation for directional control. Here, the autonomous drilling system decides on all directional changes to remain in the best zone of the reservoir, all while optimizing speed and safety parameters. Drilling autonomy is how we drill wells faster and better, always placing them in the production sweet spot. drilling autonomy is how we drill wells faster and better always placing them in the production sweet spot It's how we improve drilling efficiency by 25%-40% and help our customers produce more and reduce lifting costs. it's how we improve drilling efficiency by 25%-40% and help our customers produce more and reduce lifting costs Let me tell you about a real example. let me tell you about a real example In Libya, we have been working with Sirte, a subsidiary of the National Oil Corporation. in libya we have been working with sirte a subsidiary of the national oil corporation To accelerate well development, autonomous drilling was the answer. to accelerate well development autonomous drilling was the answer Today, Sirte produces around 110,000 barrels of oil per day with ambition to increase this further and fast. today sirte produces around 110,000 barrels of oil per day with ambition to increase this further and fast This is critical to the country's national production and economical development. this is critical to the country's national production and economical development We deployed DrillOps automation with all the drilling insights, orchestration, autonomous well placement, and bottom hole automation for directional control. we deployed drillops automation with all the drilling insights orchestration autonomous well placement and bottom hole automation for directional control Here, the autonomous drilling system decides on all directional changes to remain in the best zone of the reservoir, all while optimizing speed and safety parameters. here the autonomous drilling system decides on all directional changes to remain in the best zone of the reservoir all while optimizing speed and safety parameters It only needs 15 seconds to interpret data, decide to change the drilling plan, and send the change command to the bottom hole assembly. All of this would have taken 45 minutes without automation. If you were drilling at 100 feet per hour, it took 75 feet before the course of your well could be updated. It's like missing your exit when driving at full speed on the highway and only realizing it miles later. Tela, our agentic AI assistant, is already embedded in the system to help users who may decide to go back to manual mode. Here are the results. We doubled drilling efficiency and placed the well 100% in the reservoir. Our preferred monetization for a full drilling autonomy project like this is a performance model where we capture a portion of our customers' cost savings. As you can imagine, the revenue impact can be meaningful. It only needs 15 seconds to interpret data, decide to change the drilling plan, and send the change command to the bottom hole assembly. it only needs 15 seconds to interpret data decide to change the drilling plan and send the change command to the bottom hole assembly All of this would have taken 45 minutes without automation. all of this would have taken 45 minutes without automation If you were drilling at 100 feet per hour, it took 75 feet before the course of your well could be updated. if you were drilling at 100 feet per hour it took 75 feet before the course of your well could be updated It's like missing your exit when driving at full speed on the highway and only realizing it miles later. it's like missing your exit when driving at full speed on the highway and only realizing it miles later Tela, our agentic AI assistant, is already embedded in the system to help users who may decide to go back to manual mode. tela our agentic ai assistant is already embedded in the system to help users who may decide to go back to manual mode Here are the results. here are the results We doubled drilling efficiency and placed the well 100% in the reservoir. we doubled drilling efficiency and placed the well 100% in the reservoir Our preferred monetization for a full drilling autonomy project like this is a performance model where we capture a portion of our customers' cost savings. our preferred monetization for a full drilling autonomy project like this is a performance model where we capture a portion of our customers' cost savings As you can imagine, the revenue impact can be meaningful. as you can imagine the revenue impact can be meaningful In 2023, SLB was the first company in the world to drill a well with autonomy in Brazil. We could only deploy drilling autonomy on rigs equipped with our own control systems. To scale, we needed to develop interfaces to enable connections to a wide range of rig control systems. That is why we partnered with rig companies such as Nabors and H&P for land rigs, and Transocean and NOV for offshore operations. Thanks to this, we have the potential to automate 25% of rigs worldwide today. By 2030, we will be able to connect to 85% of the rigs. Today, we drill autonomously for 15 customers in every type of environment and geography, and we hold the most patents by far. We continue to innovate our drilling assemblies to bring new levels of control, precision, and speed. In 2023, SLB was the first company in the world to drill a well with autonomy in Brazil. in 2023 slb was the first company in the world to drill a well with autonomy in brazil We could only deploy drilling autonomy on rigs equipped with our own control systems. we could only deploy drilling autonomy on rigs equipped with our own control systems To scale, we needed to develop interfaces to enable connections to a wide range of rig control systems. to scale we needed to develop interfaces to enable connections to a wide range of rig control systems That is why we partnered with rig companies such as Nabors and H&P for land rigs, and Transocean and NOV for offshore operations. that is why we partnered with rig companies such as nabors and h&p for land rigs and transocean and nov for offshore operations Thanks to this, we have the potential to automate 25% of rigs worldwide today. thanks to this we have the potential to automate 25% of rigs worldwide today By 2030, we will be able to connect to 85% of the rigs. by 2030 we will be able to connect to 85% of the rigs Today, we drill autonomously for 15 customers in every type of environment and geography, and we hold the most patents by far. today we drill autonomously for 15 customers in every type of environment and geography and we hold the most patents by far We continue to innovate our drilling assemblies to bring new levels of control, precision, and speed. we continue to innovate our drilling assemblies to bring new levels of control precision and speed Speaking about the value we create for our customers, let's hear from one of them. Speaking about the value we create for our customers, let's hear from one of them. speaking about the value we create for our customers let's hear from one of them

Speaker 28: Today, we operate in an increasingly complex environment with growing challenges across assets and geographies and higher expectations of safety, efficiency, and performance. In this context, delivering reliable, affordable, and sustainable energy is our priority, technologies plays a key role in making this possible. Digital solutions, data, AI, and automation help us simplify complexities, improve decision-making, and accelerate execution. Technology alone is not enough. Strong partnerships are essential, SLB has proven to be a strong partner for Eni across multiple areas. Drilling is a clear example. By adopting a digital drilling model built around the SLB solution that integrates planning, real-time execution, and automation, we achieved up to 35% reduction in drilling time with safer and more predictable operations. In Congo, this approach enabled us industry-critical level of full drilling automation. Today, we operate in an increasingly complex environment with growing challenges across assets and geographies and higher expectations of safety, efficiency, and performance. today we operate in an increasingly complex environment with growing challenges across assets and geographies and higher expectations of safety efficiency and performance In this context, delivering reliable, affordable, and sustainable energy is our priority, technologies plays a key role in making this possible. in this context delivering reliable affordable and sustainable energy is our priority technologies plays a key role in making this possible Digital solutions, data, AI, and automation help us simplify complexities, improve decision-making, and accelerate execution. digital solutions data ai and automation help us simplify complexities improve decision-making and accelerate execution Technology alone is not enough. technology alone is not enough Strong partnerships are essential, SLB has proven to be a strong partner for Eni across multiple areas. strong partnerships are essential slb has proven to be a strong partner for eni across multiple areas Drilling is a clear example. drilling is a clear example By adopting a digital drilling model built around the SLB solution that integrates planning, real-time execution, and automation, we achieved up to 35% reduction in drilling time with safer and more predictable operations. by adopting a digital drilling model built around the slb solution that integrates planning real-time execution and automation we achieved up to 35% reduction in drilling time with safer and more predictable operations In Congo, this approach enabled us industry-critical level of full drilling automation. in congo this approach enabled us industry-critical level of full drilling automation We also deploy a wider set of SLB applications across the value chain, from retrievable ESP system in Mexico with reduction of downtime and cost savings, to the application of geosteering technologies in Ivory Coast to navigate within the reservoir formation and maximize well productivity. These results show how the pragmatic use of technology and innovation at scale, combined with trusted industrial collaboration like the one we have with SLB, create tangible and measurable value today and open the way to further joint opportunities across new development areas. We also deploy a wider set of SLB applications across the value chain, from retrievable ESP system in Mexico with reduction of downtime and cost savings, to the application of geosteering technologies in Ivory Coast to navigate within the reservoir formation and maximize well productivity. we also deploy a wider set of slb applications across the value chain from retrievable esp system in mexico with reduction of downtime and cost savings to the application of geosteering technologies in ivory coast to navigate within the reservoir formation and maximize well productivity These results show how the pragmatic use of technology and innovation at scale, combined with trusted industrial collaboration like the one we have with SLB, create tangible and measurable value today and open the way to further joint opportunities across new development areas. these results show how the pragmatic use of technology and innovation at scale combined with trusted industrial collaboration like the one we have with slb create tangible and measurable value today and open the way to further joint opportunities across new development areas

Speaker 3: Hearing from one of our major customers talk like this about our collaboration makes me very proud, I really look forward to seeing what else we can achieve together in the drilling space. Now, let me take you to the world of production. Complexity is heightened here. We battle disconnected equipment installed by different companies across multiple decades. A lot of it is still analog. This fragmented physical reality is found at the well level, across surface, production systems, along pipelines, and in facilities. The monitoring process will require a human to travel to the field to collect measurements. This is why connectivity is the foundation. It enables basic surveillance that generates data from SLB equipment or other providers' hardware. That's how we bring production into the digital age. Once the data stream is enabled, we can optimize equipment with digital twins. Hearing from one of our major customers talk like this about our collaboration makes me very proud, I really look forward to seeing what else we can achieve together in the drilling space. hearing from one of our major customers talk like this about our collaboration makes me very proud i really look forward to seeing what else we can achieve together in the drilling space Now, let me take you to the world of production. now let me take you to the world of production Complexity is heightened here. complexity is heightened here We battle disconnected equipment installed by different companies across multiple decades. we battle disconnected equipment installed by different companies across multiple decades A lot of it is still analog. a lot of it is still analog This fragmented physical reality is found at the well level, across surface, production systems, along pipelines, and in facilities. this fragmented physical reality is found at the well level across surface production systems along pipelines and in facilities The monitoring process will require a human to travel to the field to collect measurements. the monitoring process will require a human to travel to the field to collect measurements This is why connectivity is the foundation. this is why connectivity is the foundation It enables basic surveillance that generates data from SLB equipment or other providers' hardware. it enables basic surveillance that generates data from slb equipment or other providers' hardware That's how we bring production into the digital age. that's how we bring production into the digital age Once the data stream is enabled, we can optimize equipment with digital twins. once the data stream is enabled we can optimize equipment with digital twins We combine physics-based models with AI and our domain intelligence to identify equipment constraints sooner and deliver real-time insights to take the right action at the right time. This means more equipment uptime, leading to more production. Going further, digital enables optimization at a system level. It breaks the silos between all the equipment that coexists in a production operation, and finally connects all the elements from reservoir to point of sale to maximize production and ultimate recovery. Just like drilling, production is moving towards full autonomy, where technology not only informs intelligent decisions but also makes them. Imagine a production agent that is scanning equipment operating parameters continuously. Imagine how it could intuitively understand the impact a single change has on the entire production system. We combine physics-based models with AI and our domain intelligence to identify equipment constraints sooner and deliver real-time insights to take the right action at the right time. we combine physics-based models with ai and our domain intelligence to identify equipment constraints sooner and deliver real-time insights to take the right action at the right time This means more equipment uptime, leading to more production. this means more equipment uptime leading to more production Going further, digital enables optimization at a system level. going further digital enables optimization at a system level It breaks the silos between all the equipment that coexists in a production operation, and finally connects all the elements from reservoir to point of sale to maximize production and ultimate recovery. it breaks the silos between all the equipment that coexists in a production operation and finally connects all the elements from reservoir to point of sale to maximize production and ultimate recovery Just like drilling, production is moving towards full autonomy, where technology not only informs intelligent decisions but also makes them. just like drilling production is moving towards full autonomy where technology not only informs intelligent decisions but also makes them Imagine a production agent that is scanning equipment operating parameters continuously. imagine a production agent that is scanning equipment operating parameters continuously Imagine how it could intuitively understand the impact a single change has on the entire production system. imagine how it could intuitively understand the impact a single change has on the entire production system It acts autonomously and ensures that a single set point optimization continues to trickle through the production system to optimize it entirely, from reservoir to wells to surface equipment, pipelines, and to facilities. It sounds simple when you say it like that, but in fact, it's a very highly complex multivariable and cross-domain workflow. This is what we're actively working towards. This future is not so far ahead of us. In the U.S. Permian Basin, all wells are equipped with pumps that help lift oil to the surface. Production can decline rapidly due to the dynamic reservoir changes, and as a result, operations require continuous monitoring of artificial lift equipment. We worked with a major operator to provide real-time optimization recommendations that can be deployed on SLB and other providers' electrical submersible pumps. These recommendations are transmitted instantly to their innovative closed-loop control technology. It acts autonomously and ensures that a single set point optimization continues to trickle through the production system to optimize it entirely, from reservoir to wells to surface equipment, pipelines, and to facilities. it acts autonomously and ensures that a single set point optimization continues to trickle through the production system to optimize it entirely from reservoir to wells to surface equipment pipelines and to facilities It sounds simple when you say it like that, but in fact, it's a very highly complex multivariable and cross-domain workflow. it sounds simple when you say it like that but in fact it's a very highly complex multivariable and cross-domain workflow This is what we're actively working towards. this is what we're actively working towards This future is not so far ahead of us. this future is not so far ahead of us In the U.S. in the u.s Permian Basin, all wells are equipped with pumps that help lift oil to the surface. permian basin all wells are equipped with pumps that help lift oil to the surface Production can decline rapidly due to the dynamic reservoir changes, and as a result, operations require continuous monitoring of artificial lift equipment. production can decline rapidly due to the dynamic reservoir changes and as a result operations require continuous monitoring of artificial lift equipment We worked with a major operator to provide real-time optimization recommendations that can be deployed on SLB and other providers' electrical submersible pumps. we worked with a major operator to provide real-time optimization recommendations that can be deployed on slb and other providers' electrical submersible pumps These recommendations are transmitted instantly to their innovative closed-loop control technology. these recommendations are transmitted instantly to their innovative closed-loop control technology The system was deployed on an initial 26-well pilot. It continuously monitors well conditions, generates optimal operating set points, validates them, and implements the adjustments in a fully automated cycle. Full optimization, which initially took 29 days manually, was cut down to three days. That's 90% improvement. Equipment downtime was reduced by half. Working hours needed to monitor wells and optimize them were significantly reduced as well. Production per well was increased by 10% based on Permian average. After the success of this pilot, we signed a three-year enterprise agreement with all of the Permian ESPs and to monitor all the other lift systems in the U.S., including the gas lifts, plungers, and rod lift systems. As of today, 800 wells are actively using this closed-loop system, and we're running surveillance and optimization workflows on their 11,000 wells in the U.S. The system was deployed on an initial 26-well pilot. the system was deployed on an initial 26-well pilot It continuously monitors well conditions, generates optimal operating set points, validates them, and implements the adjustments in a fully automated cycle. it continuously monitors well conditions generates optimal operating set points validates them and implements the adjustments in a fully automated cycle Full optimization, which initially took 29 days manually, was cut down to three days. full optimization which initially took 29 days manually was cut down to three days That's 90% improvement. that's 90% improvement Equipment downtime was reduced by half. equipment downtime was reduced by half Working hours needed to monitor wells and optimize them were significantly reduced as well. working hours needed to monitor wells and optimize them were significantly reduced as well Production per well was increased by 10% based on Permian average. production per well was increased by 10% based on permian average After the success of this pilot, we signed a three-year enterprise agreement with all of the Permian ESPs and to monitor all the other lift systems in the U.S., including the gas lifts, plungers, and rod lift systems. after the success of this pilot we signed a three-year enterprise agreement with all of the permian esps and to monitor all the other lift systems in the u.s including the gas lifts plungers and rod lift systems As of today, 800 wells are actively using this closed-loop system, and we're running surveillance and optimization workflows on their 11,000 wells in the U.S. as of today 800 wells are actively using this closed-loop system and we're running surveillance and optimization workflows on their 11,000 wells in the u.s With the integration of ChampionX, we expanded our reach with the additional footprint of production equipment. Today, our install base includes 200,000 physical equipment that is either already connected or can be in the future, from artificial lift systems, which we talked about, to flow meters, chemical tanks, processing equipment, well heads, and completion hardware. All of this is our initial playground to deploy more digital production solutions. We're on a clear path to scale and this SLB install base and beyond. Looking at production and system optimization, I would like to talk to you about a digital solution we're very excited about. It truly showcases we innovate every single day. We built our existing OptiFlow tech offering, which unifies reservoir and wells into a single intelligent ecosystem to create a module exclusively available on our intelligent completion hardware. With the integration of ChampionX, we expanded our reach with the additional footprint of production equipment. with the integration of championx we expanded our reach with the additional footprint of production equipment Today, our install base includes 200,000 physical equipment that is either already connected or can be in the future, from artificial lift systems, which we talked about, to flow meters, chemical tanks, processing equipment, well heads, and completion hardware. today our install base includes 200,000 physical equipment that is either already connected or can be in the future from artificial lift systems which we talked about to flow meters chemical tanks processing equipment well heads and completion hardware All of this is our initial playground to deploy more digital production solutions. all of this is our initial playground to deploy more digital production solutions We're on a clear path to scale and this SLB install base and beyond. we're on a clear path to scale and this slb install base and beyond Looking at production and system optimization, I would like to talk to you about a digital solution we're very excited about. looking at production and system optimization i would like to talk to you about a digital solution we're very excited about It truly showcases we innovate every single day. it truly showcases we innovate every single day We built our existing OptiFlow tech offering, which unifies reservoir and wells into a single intelligent ecosystem to create a module exclusively available on our intelligent completion hardware. we built our existing optiflow tech offering which unifies reservoir and wells into a single intelligent ecosystem to create a module exclusively available on our intelligent completion hardware We're piloting it with three of our largest customers in deep water West Africa, in the Middle East, and the Caspian region. What we give them is production insights they would not have dreamed of before without overengineering their completions. Customers can see water or gas breakthrough data in real time and zone-by-zone productivity index. With the active inflow control provided by our electrical completions, which are the higher tier of our intelligent completions, they can act on these insights immediately. Production is optimized in minutes by closing, opening, or regulating from individual producing zones, all without additional intervention or workover. No more guessing and waiting, which often results in production loss. For high-producing wells like deep water wells, it promises to be a game changer. We're piloting it with three of our largest customers in deep water West Africa, in the Middle East, and the Caspian region. we're piloting it with three of our largest customers in deep water west africa in the middle east and the caspian region What we give them is production insights they would not have dreamed of before without overengineering their completions. what we give them is production insights they would not have dreamed of before without overengineering their completions Customers can see water or gas breakthrough data in real time and zone-by-zone productivity index. customers can see water or gas breakthrough data in real time and zone-by-zone productivity index With the active inflow control provided by our electrical completions, which are the higher tier of our intelligent completions, they can act on these insights immediately. with the active inflow control provided by our electrical completions which are the higher tier of our intelligent completions they can act on these insights immediately Production is optimized in minutes by closing, opening, or regulating from individual producing zones, all without additional intervention or workover. production is optimized in minutes by closing opening or regulating from individual producing zones all without additional intervention or workover No more guessing and waiting, which often results in production loss. no more guessing and waiting which often results in production loss For high-producing wells like deep water wells, it promises to be a game changer. for high-producing wells like deep water wells it promises to be a game changer It's like wearing a smartwatch and continuously monitoring your heart rate and blood pressure, getting alerts and recommendations without having to go and see a doctor to get your ECG measured. OptiFlow is patent protected. It is one of a kind because it leverages our production domain understanding and digital expertise combined with truly differentiating completion equipment. Simply put, it will be hard for our competition to replicate. According to Kimberlite research, the intelligent completion market will double in the next two to three years. SLB will quadruple installations of electrical completion specifically. Amongst our top 15 completions customers, eight of them have already adopted them with immediate reservoir control benefits. Our mission is to upsell OptiFlow on more than 80% of our electrical completions, and we know we can do it because from early pilots, all customers have already signed the subscriptions. It's like wearing a smartwatch and continuously monitoring your heart rate and blood pressure, getting alerts and recommendations without having to go and see a doctor to get your ECG measured. it's like wearing a smartwatch and continuously monitoring your heart rate and blood pressure getting alerts and recommendations without having to go and see a doctor to get your ecg measured OptiFlow is patent protected. optiflow is patent protected It is one of a kind because it leverages our production domain understanding and digital expertise combined with truly differentiating completion equipment. it is one of a kind because it leverages our production domain understanding and digital expertise combined with truly differentiating completion equipment Simply put, it will be hard for our competition to replicate. simply put it will be hard for our competition to replicate According to Kimberlite research, the intelligent completion market will double in the next two to three years. according to kimberlite research the intelligent completion market will double in the next two to three years SLB will quadruple installations of electrical completion specifically. slb will quadruple installations of electrical completion specifically Amongst our top 15 completions customers, eight of them have already adopted them with immediate reservoir control benefits. amongst our top 15 completions customers eight of them have already adopted them with immediate reservoir control benefits Our mission is to upsell OptiFlow on more than 80% of our electrical completions, and we know we can do it because from early pilots, all customers have already signed the subscriptions. our mission is to upsell optiflow on more than 80% of our electrical completions and we know we can do it because from early pilots all customers have already signed the subscriptions Traditionally, operators follow a longer adoption path from proof of concept to proof of value before committing to long-term commercial contracts. The speed of adoption we are seeing with OptiFlow is unprecedented. After all this, what are the key takeaways? It's that SLB has a unique advantage to capture the rapid growth in digital operations, and this is why we're confident. First, we have the industry's broadest operational footprint across all key environments and geographies. Every year, we drill or complete 20,000 wells, execute 100,000 intervention operations, and install more than 8,000 ESP pumps. Every drilling or production operation is an opportunity to introduce and upsell a digital solution. Second, SLB has a technology portfolio no other company in the sector can replicate. From our physical products and services to our digital platforms and solutions covering all the industry workflows. Third, we leverage our digital platforms. Traditionally, operators follow a longer adoption path from proof of concept to proof of value before committing to long-term commercial contracts. traditionally operators follow a longer adoption path from proof of concept to proof of value before committing to long-term commercial contracts The speed of adoption we are seeing with OptiFlow is unprecedented. the speed of adoption we are seeing with optiflow is unprecedented After all this, what are the key takeaways? after all this what are the key takeaways It's that SLB has a unique advantage to capture the rapid growth in digital operations, and this is why we're confident. it's that slb has a unique advantage to capture the rapid growth in digital operations and this is why we're confident First, we have the industry's broadest operational footprint across all key environments and geographies. first we have the industry's broadest operational footprint across all key environments and geographies Every year, we drill or complete 20,000 wells, execute 100,000 intervention operations, and install more than 8,000 ESP pumps. every year we drill or complete 20,000 wells execute 100,000 intervention operations and install more than 8,000 esp pumps Every drilling or production operation is an opportunity to introduce and upsell a digital solution. every drilling or production operation is an opportunity to introduce and upsell a digital solution Second, SLB has a technology portfolio no other company in the sector can replicate. second slb has a technology portfolio no other company in the sector can replicate From our physical products and services to our digital platforms and solutions covering all the industry workflows. from our physical products and services to our digital platforms and solutions covering all the industry workflows Third, we leverage our digital platforms. third we leverage our digital platforms All our digital operation solutions run on Delfi. It means that they inherit robust cybersecurity standards, cloud integration, data management, and a common edge infrastructure. This speeds up deployment and provides the foundation to scale AI in all our operations. Finally, we never stop innovating. Our process is symbiotic between innovation in hardware and software. Innovation projects are often linked, as we demonstrated with the intelligent completions example. As the digital operations mature and ingest more data, our systems are getting more intelligent. Our leadership position gets stronger, and the gap with our competition widens. The race to scale is on, and we are leading it. Let me hand over to Shashi, who will tell you more about AI, its transformative power, and where our growth efforts are focused. Thank you. All our digital operation solutions run on Delfi. all our digital operation solutions run on delfi It means that they inherit robust cybersecurity standards, cloud integration, data management, and a common edge infrastructure. it means that they inherit robust cybersecurity standards cloud integration data management and a common edge infrastructure This speeds up deployment and provides the foundation to scale AI in all our operations. this speeds up deployment and provides the foundation to scale ai in all our operations Finally, we never stop innovating. finally we never stop innovating Our process is symbiotic between innovation in hardware and software. our process is symbiotic between innovation in hardware and software Innovation projects are often linked, as we demonstrated with the intelligent completions example. innovation projects are often linked as we demonstrated with the intelligent completions example As the digital operations mature and ingest more data, our systems are getting more intelligent. as the digital operations mature and ingest more data our systems are getting more intelligent Our leadership position gets stronger, and the gap with our competition widens. our leadership position gets stronger and the gap with our competition widens The race to scale is on, and we are leading it. the race to scale is on and we are leading it Let me hand over to Shashi, who will tell you more about AI, its transformative power, and where our growth efforts are focused. let me hand over to shashi who will tell you more about ai its transformative power and where our growth efforts are focused Thank you. thank you

Speaker 32: Every molecule of oil and gas ever produced began with a question about what lies beneath the surface, answered with incomplete data, fragmented visibility, and the limits of human know-how. The industry spent decades digitizing and built real value doing it. The tools it built, the workflows, the simulations, the data systems, were designed to support decisions, not make them. They capture. They store. They model. What has been missing is the intelligence layer that connects insight to action. Agentic AI continuously reasons, interprets, and responds subsurface to surface, grounded in the physics of the domain. What once required weeks of specialist analysis now happens in hours, not by replacing expertise, but by extending it across every well, every facility, every enterprise. This only works if the AI thinks like the industry. Platforms have to be purpose-built for that trusted data, domain foundation models, and decades of industry expertise. Every molecule of oil and gas ever produced began with a question about what lies beneath the surface, answered with incomplete data, fragmented visibility, and the limits of human know-how. every molecule of oil and gas ever produced began with a question about what lies beneath the surface answered with incomplete data fragmented visibility and the limits of human know-how The industry spent decades digitizing and built real value doing it. the industry spent decades digitizing and built real value doing it The tools it built, the workflows, the simulations, the data systems, were designed to support decisions, not make them. the tools it built the workflows the simulations the data systems were designed to support decisions not make them They capture. they capture They store. they store They model. they model What has been missing is the intelligence layer that connects insight to action. what has been missing is the intelligence layer that connects insight to action Agentic AI continuously reasons, interprets, and responds subsurface to surface, grounded in the physics of the domain. agentic ai continuously reasons interprets and responds subsurface to surface grounded in the physics of the domain What once required weeks of specialist analysis now happens in hours, not by replacing expertise, but by extending it across every well, every facility, every enterprise. what once required weeks of specialist analysis now happens in hours not by replacing expertise but by extending it across every well every facility every enterprise This only works if the AI thinks like the industry. this only works if the ai thinks like the industry Platforms have to be purpose-built for that trusted data, domain foundation models, and decades of industry expertise. platforms have to be purpose-built for that trusted data domain foundation models and decades of industry expertise AI that talks like an expert and analyzes like an engineer. The result, every reservoir, every well, every pump, every facility continuously optimized. When conditions change, the system responds. Operational costs no longer scale with complexity. Assets run around the clock, proactively managed, continuously learning. The future belongs to those who add intelligence to what they've already built. We're already leading the way. AI that talks like an expert and analyzes like an engineer. ai that talks like an expert and analyzes like an engineer The result, every reservoir, every well, every pump, every facility continuously optimized. the result every reservoir every well every pump every facility continuously optimized When conditions change, the system responds. when conditions change the system responds Operational costs no longer scale with complexity. operational costs no longer scale with complexity Assets run around the clock, proactively managed, continuously learning. assets run around the clock proactively managed continuously learning The future belongs to those who add intelligence to what they've already built. the future belongs to those who add intelligence to what they've already built We're already leading the way. we're already leading the way

Speaker 19: Thank you, Cecilia. Good morning, ladies and gentlemen. I am Shashi Menon, and I lead digital technology development for SLB. Rakesh and Trygve have outlined our platforms and our market opportunities. As Rakesh was looking back through our digital history, it reminded me of my own digital journey at SLB. I had the opportunity to lead the development of our first digital platform around Excel, GPU computing with NVIDIA, cloud computing with Google, and data platforms with Microsoft. Now here I am to tell you what we are doing in this exciting world of AI that we are all living in. Today, I'm going to show you our proprietary AI technology stack. I will tell you why this is entirely unique, how we have developed specialized domain foundation models, and the secret behind why nobody else can replicate this. Let's get going. Thank you, Cecilia. thank you cecilia Good morning, ladies and gentlemen. good morning ladies and gentlemen I am Shashi Menon, and I lead digital technology development for SLB. i am shashi menon and i lead digital technology development for slb Rakesh and Trygve have outlined our platforms and our market opportunities. rakesh and trygve have outlined our platforms and our market opportunities As Rakesh was looking back through our digital history, it reminded me of my own digital journey at SLB. as rakesh was looking back through our digital history it reminded me of my own digital journey at slb I had the opportunity to lead the development of our first digital platform around Excel, GPU computing with NVIDIA, cloud computing with Google, and data platforms with Microsoft. i had the opportunity to lead the development of our first digital platform around excel gpu computing with nvidia cloud computing with google and data platforms with microsoft Now here I am to tell you what we are doing in this exciting world of AI that we are all living in. now here i am to tell you what we are doing in this exciting world of ai that we are all living in Today, I'm going to show you our proprietary AI technology stack. today i'm going to show you our proprietary ai technology stack I will tell you why this is entirely unique, how we have developed specialized domain foundation models, and the secret behind why nobody else can replicate this. i will tell you why this is entirely unique how we have developed specialized domain foundation models and the secret behind why nobody else can replicate this Let's get going. let's get going The foundation of our AI capability is an industrial platform configured specifically for the physics and data complexities of the energy sector. These are the three key elements that I want you to take away. I can tell you that these three elements are unique in our industry. No one has been successful in building these to date, not just in our industry, but across any industrial sector. They are the ones that will make or break AI in our industry. Let me explain each of these three pillars and show you how they will drive our AI transformation. Number one, the AI-ready technology stack. Let's take a look under the hood. The data layer. I think you will all agree that there is no AI without data. In our industry, more so than in any other, data is all over the place. The foundation of our AI capability is an industrial platform configured specifically for the physics and data complexities of the energy sector. the foundation of our ai capability is an industrial platform configured specifically for the physics and data complexities of the energy sector These are the three key elements that I want you to take away. these are the three key elements that i want you to take away I can tell you that these three elements are unique in our industry. i can tell you that these three elements are unique in our industry No one has been successful in building these to date, not just in our industry, but across any industrial sector. no one has been successful in building these to date not just in our industry but across any industrial sector They are the ones that will make or break AI in our industry. they are the ones that will make or break ai in our industry Let me explain each of these three pillars and show you how they will drive our AI transformation. let me explain each of these three pillars and show you how they will drive our ai transformation Number one, the AI-ready technology stack. number one the ai-ready technology stack Let's take a look under the hood. let's take a look under the hood The data layer. the data layer I think you will all agree that there is no AI without data. i think you will all agree that there is no ai without data In our industry, more so than in any other, data is all over the place. in our industry more so than in any other data is all over the place Public versus private, on-prem, on the edge, on the cloud, and pretty much everywhere. We work with mission-critical technical data like seismic, reservoir, and real-time operations data. They are stored on customer systems of record that are often proprietary, and many outside of the industry do not even know that they exist. Our customers do not want us to move or duplicate their data from their systems of record. In fact, they cannot, as data is core to their business processes, and any missteps that we make can cause serious issues. We have implemented a unique exploration and production data bridge from the ground up to honor all those customer constraints. Our data bridge is a fabric that allows us to connect to customer data sources without moving or replicating data. Public versus private, on-prem, on the edge, on the cloud, and pretty much everywhere. public versus private on-prem on the edge on the cloud and pretty much everywhere We work with mission-critical technical data like seismic, reservoir, and real-time operations data. we work with mission-critical technical data like seismic reservoir and real-time operations data They are stored on customer systems of record that are often proprietary, and many outside of the industry do not even know that they exist. they are stored on customer systems of record that are often proprietary and many outside of the industry do not even know that they exist Our customers do not want us to move or duplicate their data from their systems of record. our customers do not want us to move or duplicate their data from their systems of record In fact, they cannot, as data is core to their business processes, and any missteps that we make can cause serious issues. in fact they cannot as data is core to their business processes and any missteps that we make can cause serious issues We have implemented a unique exploration and production data bridge from the ground up to honor all those customer constraints. we have implemented a unique exploration and production data bridge from the ground up to honor all those customer constraints Our data bridge is a fabric that allows us to connect to customer data sources without moving or replicating data. our data bridge is a fabric that allows us to connect to customer data sources without moving or replicating data It is architected to work with the many, many data sources and cloud setups of our customers. It is what allows us to search, discover, access, and consume data in our AI workflows. The AI layer, it is arguably the most important. It is the magic dust on how SLB's AI differentiates. It just works for our industry. Everyone here is familiar with large language models and the weekly developments that we hear from frontier AI companies. We have seen many of our peers and our customers adopt and force-fit these models into their AI implementations. I can tell you this, that is an uphill battle to fight. Trying to decide which LLM to use, and worse, using these generic LLMs for technical workflows is really trying to boil the ocean. To uniquely solve this, we have built proprietary domain foundation models. It is architected to work with the many, many data sources and cloud setups of our customers. it is architected to work with the many many data sources and cloud setups of our customers It is what allows us to search, discover, access, and consume data in our AI workflows. it is what allows us to search discover access and consume data in our ai workflows The AI layer, it is arguably the most important. the ai layer it is arguably the most important It is the magic dust on how SLB's AI differentiates. it is the magic dust on how slb's ai differentiates It just works for our industry. it just works for our industry Everyone here is familiar with large language models and the weekly developments that we hear from frontier AI companies. everyone here is familiar with large language models and the weekly developments that we hear from frontier ai companies We have seen many of our peers and our customers adopt and force-fit these models into their AI implementations. we have seen many of our peers and our customers adopt and force-fit these models into their ai implementations I can tell you this, that is an uphill battle to fight. i can tell you this that is an uphill battle to fight Trying to decide which LLM to use, and worse, using these generic LLMs for technical workflows is really trying to boil the ocean. trying to decide which llm to use and worse using these generic llms for technical workflows is really trying to boil the ocean To uniquely solve this, we have built proprietary domain foundation models. to uniquely solve this we have built proprietary domain foundation models Not one model, but models for several of our petrotechnical domains. These models are special in three ways. One, they don't replace those generic LLMs. They actually work in tandem with any customer preferred LLM. We solve for the domain specifics while these LLMs solve for the generic. Two, our domain foundation models are purpose-built. Purpose-built because we know exactly how domain data is structured, what to look for in that data, and how to use it to deliver on the user's intent. Three, because we know which parameters are important, we know what data to feed it. We have augmented our publicly available datasets with proprietary SLB data. We have absorbed the IP and knowledge that come from decades of oil field services into these models. What does it mean for our customers? It is simple. Not one model, but models for several of our petrotechnical domains. not one model but models for several of our petrotechnical domains These models are special in three ways. these models are special in three ways One, they don't replace those generic LLMs. one they don't replace those generic llms They actually work in tandem with any customer preferred LLM. they actually work in tandem with any customer preferred llm We solve for the domain specifics while these LLMs solve for the generic. we solve for the domain specifics while these llms solve for the generic Two, our domain foundation models are purpose-built. two our domain foundation models are purpose-built Purpose-built because we know exactly how domain data is structured, what to look for in that data, and how to use it to deliver on the user's intent. purpose-built because we know exactly how domain data is structured what to look for in that data and how to use it to deliver on the user's intent Three, because we know which parameters are important, we know what data to feed it. three because we know which parameters are important we know what data to feed it We have augmented our publicly available datasets with proprietary SLB data. we have augmented our publicly available datasets with proprietary slb data We have absorbed the IP and knowledge that come from decades of oil field services into these models. we have absorbed the ip and knowledge that come from decades of oil field services into these models What does it mean for our customers? what does it mean for our customers It is simple. it is simple Our domain foundation models give them a powerful base model that is continuously updated. They can even refine these models within our platforms with their own data to customize them for their own assets. Three, the user experience layer. The key here is the Tela Canvas. Think of it as the ultimate industry Copilot. You all know how ingrained ChatGPT, Claude, Gemini have become in our day-to-day activities. Our users will soon find Tela indispensable because it is just as easy to use, and it is already integrated into the products that they use daily. Now, even more so because Tela understands their technical context, has strong guardrails that ensures that it never goes off-rails, and is built using domain benchmarks to ensure that it stays within the bounds of domain science. The second key element is our domain AI. Our domain foundation models give them a powerful base model that is continuously updated. our domain foundation models give them a powerful base model that is continuously updated They can even refine these models within our platforms with their own data to customize them for their own assets. they can even refine these models within our platforms with their own data to customize them for their own assets Three, the user experience layer. three the user experience layer The key here is the Tela Canvas. the key here is the tela canvas Think of it as the ultimate industry Copilot. think of it as the ultimate industry copilot You all know how ingrained ChatGPT, Claude, Gemini have become in our day-to-day activities. you all know how ingrained chatgpt claude gemini have become in our day-to-day activities Our users will soon find Tela indispensable because it is just as easy to use, and it is already integrated into the products that they use daily. our users will soon find tela indispensable because it is just as easy to use and it is already integrated into the products that they use daily Now, even more so because Tela understands their technical context, has strong guardrails that ensures that it never goes off-rails, and is built using domain benchmarks to ensure that it stays within the bounds of domain science. now even more so because tela understands their technical context has strong guardrails that ensures that it never goes off-rails and is built using domain benchmarks to ensure that it stays within the bounds of domain science The second key element is our domain AI. the second key element is our domain ai Our AI implementations are structured to meet our customers wherever they are in their AI readiness. For organizations beginning their AI transition, we offer conversational experiences that extract insights from their data, from their project histories, and from their operational context. This is powered by an energy-specific LLM infrastructure that is trained on SLB's technical data, documentation, intellectual property, and essentially, our oil field experience. The barrier for adoption to our customers is very low, and the value for them is immediate. For those customers who are further along in their technical journey, our software embeds dedicated AI agents powered by our domain foundation models, skills, and tools. These provide high-value engineering recommendations while keeping the user in control of the decisions. For those customers that are advanced operators, our agentic framework runs fully autonomous workflows. Our AI implementations are structured to meet our customers wherever they are in their AI readiness. our ai implementations are structured to meet our customers wherever they are in their ai readiness For organizations beginning their AI transition, we offer conversational experiences that extract insights from their data, from their project histories, and from their operational context. for organizations beginning their ai transition we offer conversational experiences that extract insights from their data from their project histories and from their operational context This is powered by an energy-specific LLM infrastructure that is trained on SLB's technical data, documentation, intellectual property, and essentially, our oil field experience. this is powered by an energy-specific llm infrastructure that is trained on slb's technical data documentation intellectual property and essentially our oil field experience The barrier for adoption to our customers is very low, and the value for them is immediate. the barrier for adoption to our customers is very low and the value for them is immediate For those customers who are further along in their technical journey, our software embeds dedicated AI agents powered by our domain foundation models, skills, and tools. for those customers who are further along in their technical journey our software embeds dedicated ai agents powered by our domain foundation models skills and tools These provide high-value engineering recommendations while keeping the user in control of the decisions. these provide high-value engineering recommendations while keeping the user in control of the decisions For those customers that are advanced operators, our agentic framework runs fully autonomous workflows. for those customers that are advanced operators our agentic framework runs fully autonomous workflows They observe, plan, generate, act, and learn loop, but they are fully constrained at every step by domain science and physical guardrails. These agents are trained on validated domain data, they offer an assurance and accuracy that is unique to SLB. The third key element is our technology partnership. You heard from Trygve earlier about the breadth of our partner ecosystem. I want to go deeper into one in particular. Our partnership with NVIDIA is special. It is nearly a 20-year-old joint engineering program. We have direct access to their top engineers, and they choose to work with us for one specific reason. We bring the unique domain physics that is needed to push the boundaries of digital in energy. Together, we are building the Tela AI factory for energy to bring the most powerful set of agentic AI implementations in the industry to our customers. They observe, plan, generate, act, and learn loop, but they are fully constrained at every step by domain science and physical guardrails. they observe plan generate act and learn loop but they are fully constrained at every step by domain science and physical guardrails These agents are trained on validated domain data, they offer an assurance and accuracy that is unique to SLB. these agents are trained on validated domain data they offer an assurance and accuracy that is unique to slb The third key element is our technology partnership. the third key element is our technology partnership You heard from Trygve earlier about the breadth of our partner ecosystem. you heard from trygve earlier about the breadth of our partner ecosystem I want to go deeper into one in particular. i want to go deeper into one in particular Our partnership with NVIDIA is special. our partnership with nvidia is special It is nearly a 20-year-old joint engineering program. it is nearly a 20-year-old joint engineering program We have direct access to their top engineers, and they choose to work with us for one specific reason. we have direct access to their top engineers and they choose to work with us for one specific reason We bring the unique domain physics that is needed to push the boundaries of digital in energy. we bring the unique domain physics that is needed to push the boundaries of digital in energy Together, we are building the Tela AI factory for energy to bring the most powerful set of agentic AI implementations in the industry to our customers. together we are building the tela ai factory for energy to bring the most powerful set of agentic ai implementations in the industry to our customers Let me be clear what this integration means. Guaranteed peak performance. Every domain foundation model we produce is optimized to be the absolute highest performing model in the industry. NVIDIA engineers are actively taking our source code and tuning it to run optimally for today's Blackwell chips, and they're already future-proofing it for tomorrow's Vera Rubin architecture. We are fusing the world's leading AI computing architecture directly with our unparalleled domain data and science. No one else can do this at scale today. It creates a competitive moat that simply cannot be replicated. We deliver these AI capabilities through two distinct user experiences, each one designed for a different mode of working. Tela Embedded integrates agentic AI directly in our existing widely deployed software, Petrel, Techlog, Trillo, OptiFlow, et cetera. Our users access conversational and agentic tools natively within these applications that they use every day. Let me be clear what this integration means. let me be clear what this integration means Guaranteed peak performance. guaranteed peak performance Every domain foundation model we produce is optimized to be the absolute highest performing model in the industry. every domain foundation model we produce is optimized to be the absolute highest performing model in the industry NVIDIA engineers are actively taking our source code and tuning it to run optimally for today's Blackwell chips, and they're already future-proofing it for tomorrow's Vera Rubin architecture. nvidia engineers are actively taking our source code and tuning it to run optimally for today's blackwell chips and they're already future-proofing it for tomorrow's vera rubin architecture We are fusing the world's leading AI computing architecture directly with our unparalleled domain data and science. we are fusing the world's leading ai computing architecture directly with our unparalleled domain data and science No one else can do this at scale today. no one else can do this at scale today It creates a competitive moat that simply cannot be replicated. it creates a competitive moat that simply cannot be replicated We deliver these AI capabilities through two distinct user experiences, each one designed for a different mode of working. we deliver these ai capabilities through two distinct user experiences each one designed for a different mode of working Tela Embedded integrates agentic AI directly in our existing widely deployed software, Petrel, Techlog, Trillo, OptiFlow, et cetera. tela embedded integrates agentic ai directly in our existing widely deployed software petrel techlog trillo optiflow et cetera Our users access conversational and agentic tools natively within these applications that they use every day. our users access conversational and agentic tools natively within these applications that they use every day This drives immediate productivity gains and reinforces the value of our software for our users. This provides that indispensability that I talked about earlier. It is simply there for them to use. Tela Canvas is a standalone experience designed for broader cross-functional use. It works across application boundaries and data silos, orchestrating complex end-to-end technical workflows by combining AI with the physics-based domain science that forms the core of our software portfolio. Where Tela Embedded enhances individual application workflows, Tela Canvas connects them. Our customers can choose between rapid transaction-focused interactions via Tela Canvas or deep, immersive engineering workflows within our core applications. Both run on identical agentic AI backbone, the same domain foundation models, the same physical guardrails, and the same data infrastructure. Now let me show you what this looks like in practice, starting with planning. This drives immediate productivity gains and reinforces the value of our software for our users. this drives immediate productivity gains and reinforces the value of our software for our users This provides that indispensability that I talked about earlier. this provides that indispensability that i talked about earlier It is simply there for them to use. it is simply there for them to use Tela Canvas is a standalone experience designed for broader cross-functional use. tela canvas is a standalone experience designed for broader cross-functional use It works across application boundaries and data silos, orchestrating complex end-to-end technical workflows by combining AI with the physics-based domain science that forms the core of our software portfolio. it works across application boundaries and data silos orchestrating complex end-to-end technical workflows by combining ai with the physics-based domain science that forms the core of our software portfolio Where Tela Embedded enhances individual application workflows, Tela Canvas connects them. where tela embedded enhances individual application workflows tela canvas connects them Our customers can choose between rapid transaction-focused interactions via Tela Canvas or deep, immersive engineering workflows within our core applications. our customers can choose between rapid transaction-focused interactions via tela canvas or deep immersive engineering workflows within our core applications Both run on identical agentic AI backbone, the same domain foundation models, the same physical guardrails, and the same data infrastructure. both run on identical agentic ai backbone the same domain foundation models the same physical guardrails and the same data infrastructure Now let me show you what this looks like in practice, starting with planning. now let me show you what this looks like in practice starting with planning Our planning solutions and workflows are driven by an extensive portfolio of subsurface agents, models, and specialized tools that cover the full spectrum of technical workflows used in exploration and field development. They provide a very comprehensive coverage of the key domains across geophysics, petrophysics, geology, and reservoir engineering that Rakesh talked about earlier. Let's see an example of these planning agents in action within the Tela Canvas and connecting to Petrel, our leading subsurface platform. Our planning solutions and workflows are driven by an extensive portfolio of subsurface agents, models, and specialized tools that cover the full spectrum of technical workflows used in exploration and field development. our planning solutions and workflows are driven by an extensive portfolio of subsurface agents models and specialized tools that cover the full spectrum of technical workflows used in exploration and field development They provide a very comprehensive coverage of the key domains across geophysics, petrophysics, geology, and reservoir engineering that Rakesh talked about earlier. they provide a very comprehensive coverage of the key domains across geophysics petrophysics geology and reservoir engineering that rakesh talked about earlier Let's see an example of these planning agents in action within the Tela Canvas and connecting to Petrel, our leading subsurface platform. let's see an example of these planning agents in action within the tela canvas and connecting to petrel our leading subsurface platform

Speaker 32: Log then. Tela immediately notifies them of new well data available for the southern part of Block C14. With a single click, they choose to view the data. The data is loaded into the IVAAP log canvas. Tela recognizes that this data has not been reviewed yet and offers to run a quality control check. The user agrees, and the well data is conditioned and QC'd automatically. With the data now ready, the user requests a porosity prediction for the reservoir interval. Using the domain foundation model, Tela predicts porosity and updates the canvas with a new log. The user asks for a list of seismic data in the area and guidance on which dataset is most suitable for structural interpretation and trap detection. Log then. log then Tela immediately notifies them of new well data available for the southern part of Block C14. tela immediately notifies them of new well data available for the southern part of block c14 With a single click, they choose to view the data. with a single click they choose to view the data The data is loaded into the IVAAP log canvas. the data is loaded into the ivaap log canvas Tela recognizes that this data has not been reviewed yet and offers to run a quality control check. tela recognizes that this data has not been reviewed yet and offers to run a quality control check The user agrees, and the well data is conditioned and QC'd automatically. the user agrees and the well data is conditioned and qc'd automatically With the data now ready, the user requests a porosity prediction for the reservoir interval. with the data now ready the user requests a porosity prediction for the reservoir interval Using the domain foundation model, Tela predicts porosity and updates the canvas with a new log. using the domain foundation model tela predicts porosity and updates the canvas with a new log The user asks for a list of seismic data in the area and guidance on which dataset is most suitable for structural interpretation and trap detection. the user asks for a list of seismic data in the area and guidance on which dataset is most suitable for structural interpretation and trap detection Tela quickly provides a list of seismic cubes and highlights the BO Carry dataset as the best option for this task. With the dataset selected, the user asks Tela to identify a structural trap. Leveraging the domain foundation model, Tela detects a structural trap in the Vinton Dome area and displays the section. The structural trap is visualized, and Tela suggests performing a more detailed fault analysis. However, the user decides to handle the fault analysis manually and instead requests a search for fluid contacts within the trap. Using the anomaly detector agent, Tela identifies a pay zone and presents a 3D visualization of the area, providing critical insights for further evaluation. To refine the structural interpretation and prospect analysis, the user requests to load the new well and seismic data into Petrel. Tela seamlessly transfers all data, enabling the user to continue their work with ML-assisted seismic interpretation tools. Tela quickly provides a list of seismic cubes and highlights the BO Carry dataset as the best option for this task. tela quickly provides a list of seismic cubes and highlights the bo carry dataset as the best option for this task With the dataset selected, the user asks Tela to identify a structural trap. with the dataset selected the user asks tela to identify a structural trap Leveraging the domain foundation model, Tela detects a structural trap in the Vinton Dome area and displays the section. leveraging the domain foundation model tela detects a structural trap in the vinton dome area and displays the section The structural trap is visualized, and Tela suggests performing a more detailed fault analysis. the structural trap is visualized and tela suggests performing a more detailed fault analysis However, the user decides to handle the fault analysis manually and instead requests a search for fluid contacts within the trap. however the user decides to handle the fault analysis manually and instead requests a search for fluid contacts within the trap Using the anomaly detector agent, Tela identifies a pay zone and presents a 3D visualization of the area, providing critical insights for further evaluation. using the anomaly detector agent tela identifies a pay zone and presents a 3d visualization of the area providing critical insights for further evaluation To refine the structural interpretation and prospect analysis, the user requests to load the new well and seismic data into Petrel. to refine the structural interpretation and prospect analysis the user requests to load the new well and seismic data into petrel Tela seamlessly transfers all data, enabling the user to continue their work with ML-assisted seismic interpretation tools. tela seamlessly transfers all data enabling the user to continue their work with ml-assisted seismic interpretation tools In the Petrel application, the user has access to Tela in the side panel, and the conversation can continue. In the Petrel application, the user has access to Tela in the side panel, and the conversation can continue. in the petrel application the user has access to tela in the side panel and the conversation can continue

Speaker 19: You just saw a glimpse of Tela in action, both as a Tela Canvas as well as Tela Embedded in Petrel. It shows how a combination of domain foundation models and other AI models integrated into a project workflow can completely transform them. I want you to think why this is so differentiating, why this demo could not have been done just six months ago. A typical exploration workflow to directly detect hydrocarbon-rich areas in the subsurface takes a team of geoscientists weeks to execute. We are transforming these complex nine steps into two simple clicks, almost magically. We are compressing weeks of complex analysis into a few hours, while covering a broader range of scenarios than was previously practical. Let me tell you how this works. You've heard me say domain foundation models several times. You just saw a glimpse of Tela in action, both as a Tela Canvas as well as Tela Embedded in Petrel. you just saw a glimpse of tela in action both as a tela canvas as well as tela embedded in petrel It shows how a combination of domain foundation models and other AI models integrated into a project workflow can completely transform them. it shows how a combination of domain foundation models and other ai models integrated into a project workflow can completely transform them I want you to think why this is so differentiating, why this demo could not have been done just six months ago. i want you to think why this is so differentiating why this demo could not have been done just six months ago A typical exploration workflow to directly detect hydrocarbon-rich areas in the subsurface takes a team of geoscientists weeks to execute. a typical exploration workflow to directly detect hydrocarbon-rich areas in the subsurface takes a team of geoscientists weeks to execute We are transforming these complex nine steps into two simple clicks, almost magically. we are transforming these complex nine steps into two simple clicks almost magically We are compressing weeks of complex analysis into a few hours, while covering a broader range of scenarios than was previously practical. we are compressing weeks of complex analysis into a few hours while covering a broader range of scenarios than was previously practical Let me tell you how this works. let me tell you how this works You've heard me say domain foundation models several times. you've heard me say domain foundation models several times Let me explain what they are and the key role that they play in our AI implementations by using the seismic domain foundation model as an example. Seismic data is core to most exploration and field development workflows. However, seismic data modalities, its structure, and its format are very unique to our industry, and large language models are unable to work with them. What we did was we started with a base vision transformer model. We adapted it to handle those seismic data modalities. We incorporated seismic and geoscience domain priors and context, we trained it with public and SLB multi-client seismic datasets. The outcome is a rich and capable seismic foundation model with less than 1 billion parameters. For reference, leading frontier models are well beyond 1 trillion parameters today. The small parameter count means our models are cost-effective to develop and to operationalize. Let me explain what they are and the key role that they play in our AI implementations by using the seismic domain foundation model as an example. let me explain what they are and the key role that they play in our ai implementations by using the seismic domain foundation model as an example Seismic data is core to most exploration and field development workflows. seismic data is core to most exploration and field development workflows However, seismic data modalities, its structure, and its format are very unique to our industry, and large language models are unable to work with them. however seismic data modalities its structure and its format are very unique to our industry and large language models are unable to work with them What we did was we started with a base vision transformer model. what we did was we started with a base vision transformer model We adapted it to handle those seismic data modalities. we adapted it to handle those seismic data modalities We incorporated seismic and geoscience domain priors and context, we trained it with public and SLB multi-client seismic datasets. we incorporated seismic and geoscience domain priors and context we trained it with public and slb multi-client seismic datasets The outcome is a rich and capable seismic foundation model with less than 1 billion parameters. the outcome is a rich and capable seismic foundation model with less than 1 billion parameters For reference, leading frontier models are well beyond 1 trillion parameters today. for reference leading frontier models are well beyond 1 trillion parameters today The small parameter count means our models are cost-effective to develop and to operationalize. the small parameter count means our models are cost-effective to develop and to operationalize It will also allow our customers to then fine-tune these models with their data for their continued use in Delfi and Lumi platforms. As in planning, our operational execution relies on a dedicated, scalable portfolio of operational agents, models, and tools. These cover our drilling operations in our DrillOps family of products. They enable the increasing autonomy of complex operations, such as real-time geosteering that Cecilia talked about. On the production side, agentic workflows form the core of our Opti Suite of production offerings. These range from lift operations in wells to pipelines and networks to complex facility operations like FPSOs. Let me exemplify this from a deployment that we did for a customer in the Middle East. In traditional operating models, engineers must manually trigger, review, and process data to manage facility of equipment. It will also allow our customers to then fine-tune these models with their data for their continued use in Delfi and Lumi platforms. it will also allow our customers to then fine-tune these models with their data for their continued use in delfi and lumi platforms As in planning, our operational execution relies on a dedicated, scalable portfolio of operational agents, models, and tools. as in planning our operational execution relies on a dedicated scalable portfolio of operational agents models and tools These cover our drilling operations in our DrillOps family of products. these cover our drilling operations in our drillops family of products They enable the increasing autonomy of complex operations, such as real-time geosteering that Cecilia talked about. they enable the increasing autonomy of complex operations such as real-time geosteering that cecilia talked about On the production side, agentic workflows form the core of our Opti Suite of production offerings. on the production side agentic workflows form the core of our opti suite of production offerings These range from lift operations in wells to pipelines and networks to complex facility operations like FPSOs. these range from lift operations in wells to pipelines and networks to complex facility operations like fpsos Let me exemplify this from a deployment that we did for a customer in the Middle East. let me exemplify this from a deployment that we did for a customer in the middle east In traditional operating models, engineers must manually trigger, review, and process data to manage facility of equipment. in traditional operating models engineers must manually trigger review and process data to manage facility of equipment This is an incredibly frustrating and monotonous activity for a production engineer, while for the company, this means operational adjustments can only be made when there is someone at the desk. What Tela does is that it converts these manual actions into autonomous evergreen loops, reserving human intervention only for high-value capital decisions. You might say, "So what?" When we talk about a production asset, we are talking about a lot of equipment. These come from different vendors, are of different vintages, each with different sensors, working with different parameters and data formats. All of them are being used differently in different conditions. Leveraging agentic AI is the only way to reach operational autonomy at scale while still retaining human oversight. We can do this. We can do this because our equipment digital twins are trained on real-world physics and are validated through continuous iterations. This is an incredibly frustrating and monotonous activity for a production engineer, while for the company, this means operational adjustments can only be made when there is someone at the desk. this is an incredibly frustrating and monotonous activity for a production engineer while for the company this means operational adjustments can only be made when there is someone at the desk What Tela does is that it converts these manual actions into autonomous evergreen loops, reserving human intervention only for high-value capital decisions. what tela does is that it converts these manual actions into autonomous evergreen loops reserving human intervention only for high-value capital decisions You might say, "So what?" When we talk about a production asset, we are talking about a lot of equipment. you might say "so what?" when we talk about a production asset we are talking about a lot of equipment These come from different vendors, are of different vintages, each with different sensors, working with different parameters and data formats. these come from different vendors are of different vintages each with different sensors working with different parameters and data formats All of them are being used differently in different conditions. all of them are being used differently in different conditions Leveraging agentic AI is the only way to reach operational autonomy at scale while still retaining human oversight. leveraging agentic ai is the only way to reach operational autonomy at scale while still retaining human oversight We can do this. we can do this We can do this because our equipment digital twins are trained on real-world physics and are validated through continuous iterations. we can do this because our equipment digital twins are trained on real-world physics and are validated through continuous iterations We can do this because we are OEM-agnostic and can support equipment from a wide range of providers. We can do this because we can model and simulate at the asset or system level. These enable round-the-clock facility optimization, directly lowering operating risks, minimizing unplanned downtime, and maximizing barrels produced. You will soon hear from Stéphane our broader monetization strategy, but let me be a bit bombastic for a moment. Every single agent, every model, every tool that a customer uses within our ecosystem, we have implemented the platform so that we can track their consumption every single time at scale. That tracking and provenance is exactly why and how we can monetize AI. We do this through four distinct channels. We already talked about Tela Embedded into our existing widely deployed software platforms. We monetize through upselling Tela subscriptions and then on the consumption of agentic workflows. We can do this because we are OEM-agnostic and can support equipment from a wide range of providers. we can do this because we are oem-agnostic and can support equipment from a wide range of providers We can do this because we can model and simulate at the asset or system level. we can do this because we can model and simulate at the asset or system level These enable round-the-clock facility optimization, directly lowering operating risks, minimizing unplanned downtime, and maximizing barrels produced. these enable round-the-clock facility optimization directly lowering operating risks minimizing unplanned downtime and maximizing barrels produced You will soon hear from Stéphane our broader monetization strategy, but let me be a bit bombastic for a moment. you will soon hear from stéphane our broader monetization strategy but let me be a bit bombastic for a moment Every single agent, every model, every tool that a customer uses within our ecosystem, we have implemented the platform so that we can track their consumption every single time at scale. every single agent every model every tool that a customer uses within our ecosystem we have implemented the platform so that we can track their consumption every single time at scale That tracking and provenance is exactly why and how we can monetize AI. that tracking and provenance is exactly why and how we can monetize ai We do this through four distinct channels. we do this through four distinct channels We already talked about Tela Embedded into our existing widely deployed software platforms. we already talked about tela embedded into our existing widely deployed software platforms We monetize through upselling Tela subscriptions and then on the consumption of agentic workflows. we monetize through upselling tela subscriptions and then on the consumption of agentic workflows Tela Canvas opens a new channel for monetization, where a base subscription paired with consumption-based pricing allows us to cross-sell to the existing customer base. It also creates new sales opportunities with those customers that find adopting platforms like Petrel to be a heavy lift. Going beyond these two channels, we also develop fit-for-purpose AI workflows for our customers through our innovation factory model, a network of seven AI centers of excellences around the world. These solutions are then deployed with the customer's Lumi and Delfi environments, creating long-term platform stickiness and ongoing consumption. Finally, the digital marketplace that we announced on Monday. It enables a platform business model for SLB and verified third-party developers to offer specialized agents, models, and applications that can be deployed in our digital ecosystem. Tela Canvas opens a new channel for monetization, where a base subscription paired with consumption-based pricing allows us to cross-sell to the existing customer base. tela canvas opens a new channel for monetization where a base subscription paired with consumption-based pricing allows us to cross-sell to the existing customer base It also creates new sales opportunities with those customers that find adopting platforms like Petrel to be a heavy lift. it also creates new sales opportunities with those customers that find adopting platforms like petrel to be a heavy lift Going beyond these two channels, we also develop fit-for-purpose AI workflows for our customers through our innovation factory model, a network of seven AI centers of excellences around the world. going beyond these two channels we also develop fit-for-purpose ai workflows for our customers through our innovation factory model a network of seven ai centers of excellences around the world These solutions are then deployed with the customer's Lumi and Delfi environments, creating long-term platform stickiness and ongoing consumption. these solutions are then deployed with the customer's lumi and delfi environments creating long-term platform stickiness and ongoing consumption Finally, the digital marketplace that we announced on Monday. finally the digital marketplace that we announced on monday It enables a platform business model for SLB and verified third-party developers to offer specialized agents, models, and applications that can be deployed in our digital ecosystem. it enables a platform business model for slb and verified third-party developers to offer specialized agents models and applications that can be deployed in our digital ecosystem We monetize through revenue sharing driven by consumption, a high margin, scalable channel that will grow with the ecosystem itself. As I conclude, I want to emphasize one critical truth. Today, no other company in our industry can do what SLB has accomplished. We did not ride the wave of generic AI models. We built proprietary domain foundation models from the ground up. We did not ask the industry to rewrite their operations. We embedded intelligence directly into the applications that tens of thousands of geoscientists and engineers trust every day. We have created an agentic framework that is open for our customers to extend and yet rigorous to operate autonomously within physical constraints. This combination of proprietary models, trusted platforms, deep domain science, augmented by strong digital partnership is what positions SLB to lead the commercialization of AI in our industry. We monetize through revenue sharing driven by consumption, a high margin, scalable channel that will grow with the ecosystem itself. we monetize through revenue sharing driven by consumption a high margin scalable channel that will grow with the ecosystem itself As I conclude, I want to emphasize one critical truth. as i conclude i want to emphasize one critical truth Today, no other company in our industry can do what SLB has accomplished. today no other company in our industry can do what slb has accomplished We did not ride the wave of generic AI models. we did not ride the wave of generic ai models We built proprietary domain foundation models from the ground up. we built proprietary domain foundation models from the ground up We did not ask the industry to rewrite their operations. we did not ask the industry to rewrite their operations We embedded intelligence directly into the applications that tens of thousands of geoscientists and engineers trust every day. we embedded intelligence directly into the applications that tens of thousands of geoscientists and engineers trust every day We have created an agentic framework that is open for our customers to extend and yet rigorous to operate autonomously within physical constraints. we have created an agentic framework that is open for our customers to extend and yet rigorous to operate autonomously within physical constraints This combination of proprietary models, trusted platforms, deep domain science, augmented by strong digital partnership is what positions SLB to lead the commercialization of AI in our industry. this combination of proprietary models trusted platforms deep domain science augmented by strong digital partnership is what positions slb to lead the commercialization of ai in our industry It is a position that will allow us to be first and go further once again. Now, let me welcome Stéphane to the stage to discuss the financial impact of our digital business. Thank you. It is a position that will allow us to be first and go further once again. it is a position that will allow us to be first and go further once again Now, let me welcome Stéphane to the stage to discuss the financial impact of our digital business. now let me welcome stéphane to the stage to discuss the financial impact of our digital business Thank you. thank you

Speaker 21: Good morning, everyone, and thank you for joining us today. Before we start, let me briefly step back and review the story you've heard so far. We have discussed the pivotal role of digital in our industry and the differentiated position SLB has built over time. You have seen how we are leveraging our platforms and applications across planning and operations workflows. You have heard about the opportunity to scale AI across our portfolio to unlock even greater value. What I would like to do now is bring that story together through a financial lens. Over the next few minutes, I will focus on three areas. First, the digital profile of our digital business. The financial profile of our digital business. Second, the significant market opportunity ahead of us and how we plan to monetize it. Finally, our 2030 financial ambitions. Good morning, everyone, and thank you for joining us today. good morning everyone and thank you for joining us today Before we start, let me briefly step back and review the story you've heard so far. before we start let me briefly step back and review the story you've heard so far We have discussed the pivotal role of digital in our industry and the differentiated position SLB has built over time. we have discussed the pivotal role of digital in our industry and the differentiated position slb has built over time You have seen how we are leveraging our platforms and applications across planning and operations workflows. you have seen how we are leveraging our platforms and applications across planning and operations workflows You have heard about the opportunity to scale AI across our portfolio to unlock even greater value. you have heard about the opportunity to scale ai across our portfolio to unlock even greater value What I would like to do now is bring that story together through a financial lens. what i would like to do now is bring that story together through a financial lens Over the next few minutes, I will focus on three areas. over the next few minutes i will focus on three areas First, the digital profile of our digital business. first the digital profile of our digital business The financial profile of our digital business. the financial profile of our digital business Second, the significant market opportunity ahead of us and how we plan to monetize it. second the significant market opportunity ahead of us and how we plan to monetize it Finally, our 2030 financial ambitions. finally our 2030 financial ambitions The key takeaway is this: digital has become a meaningful contributor to SLB's financial performance in the past few years, and we continue to see significant runway ahead with accretive growth and continued margin expansion. Let me begin with where the business stands today. In 2025, digital generated approximately $2.7 billion of revenue, more than $900 million of adjusted EBITDA, and an adjusted EBITDA margin of 35%. It also reached approximately $1 billion in annual recurring revenue on a trailing 12-month basis. What is most important is the quality of this growth. Since 2021, digital revenue has grown at a 16% compound annual growth rate, well above the oilfield services market and SLB's overall growth during the same period. Adjusted EBITDA grew even faster at a 23% CAGR compared with approximately 14% for SLB overall, demonstrating digital's strong operating leverage and differentiated earnings power. The key takeaway is this: digital has become a meaningful contributor to SLB's financial performance in the past few years, and we continue to see significant runway ahead with accretive growth and continued margin expansion. the key takeaway is this digital has become a meaningful contributor to slb's financial performance in the past few years and we continue to see significant runway ahead with accretive growth and continued margin expansion Let me begin with where the business stands today. let me begin with where the business stands today In 2025, digital generated approximately $2.7 billion of revenue, more than $900 million of adjusted EBITDA, and an adjusted EBITDA margin of 35%. in 2025 digital generated approximately $2.7 billion of revenue more than $900 million of adjusted ebitda and an adjusted ebitda margin of 35% It also reached approximately $1 billion in annual recurring revenue on a trailing 12-month basis. it also reached approximately $1 billion in annual recurring revenue on a trailing 12-month basis What is most important is the quality of this growth. what is most important is the quality of this growth Since 2021, digital revenue has grown at a 16% compound annual growth rate, well above the oilfield services market and SLB's overall growth during the same period. since 2021 digital revenue has grown at a 16% compound annual growth rate well above the oilfield services market and slb's overall growth during the same period Adjusted EBITDA grew even faster at a 23% CAGR compared with approximately 14% for SLB overall, demonstrating digital's strong operating leverage and differentiated earnings power. adjusted ebitda grew even faster at a 23% cagr compared with approximately 14% for slb overall demonstrating digital's strong operating leverage and differentiated earnings power The margin profile you see here already reflects a meaningful share of the cost required to support growth as the research and engineering spend is directly expensed. That translates into very strong cash generation and effectively makes digital the division with the highest return on capital employed in the company. What digital brings to SLB is very clear. It adds growth, it lifts margins, and it delivers very attractive returns. Let me now describe our digital revenue footprint. One of the defining strengths of this business is that it is diversified across geographies, customer types and revenue categories. That matters because it gives us a broader opportunity set, greater resilience and multiple paths to growth. Today, our digital business serves more than 1,500 customers, including more than 90 of the world's top 100 oil and gas producers. The margin profile you see here already reflects a meaningful share of the cost required to support growth as the research and engineering spend is directly expensed. the margin profile you see here already reflects a meaningful share of the cost required to support growth as the research and engineering spend is directly expensed That translates into very strong cash generation and effectively makes digital the division with the highest return on capital employed in the company. that translates into very strong cash generation and effectively makes digital the division with the highest return on capital employed in the company What digital brings to SLB is very clear. what digital brings to slb is very clear It adds growth, it lifts margins, and it delivers very attractive returns. it adds growth it lifts margins and it delivers very attractive returns Let me now describe our digital revenue footprint. let me now describe our digital revenue footprint One of the defining strengths of this business is that it is diversified across geographies, customer types and revenue categories. one of the defining strengths of this business is that it is diversified across geographies customer types and revenue categories That matters because it gives us a broader opportunity set, greater resilience and multiple paths to growth. that matters because it gives us a broader opportunity set greater resilience and multiple paths to growth Today, our digital business serves more than 1,500 customers, including more than 90 of the world's top 100 oil and gas producers. today our digital business serves more than 1,500 customers including more than 90 of the world's top 100 oil and gas producers That is a strong install base and a solid foundation for growth. Geographically, the business has broad exposure across the Middle East and Asia, Europe and Africa, Latin America and North America. Our customer mix is also well-balanced across national oil companies, independents and majors. That mix is important. With national oil company and independents, we already see strong digital adoption, particularly in planning workflows. With the majors, we see a meaningful runway. As some customers move away from internally developed systems towards scalable enterprise-grade platforms that can support broader digital transformation. Finally, from a revenue category perspective, platform as an application represents approximately 40% of digital revenue, followed by professional services, digital operations and digital exploration. That mix will evolve as digital operations continue to scale. We expect it to become the largest part of the business over time, as I will describe momentarily. That is a strong install base and a solid foundation for growth. that is a strong install base and a solid foundation for growth Geographically, the business has broad exposure across the Middle East and Asia, Europe and Africa, Latin America and North America. geographically the business has broad exposure across the middle east and asia europe and africa latin america and north america Our customer mix is also well-balanced across national oil companies, independents and majors. our customer mix is also well-balanced across national oil companies independents and majors That mix is important. that mix is important With national oil company and independents, we already see strong digital adoption, particularly in planning workflows. with national oil company and independents we already see strong digital adoption particularly in planning workflows With the majors, we see a meaningful runway. with the majors we see a meaningful runway As some customers move away from internally developed systems towards scalable enterprise-grade platforms that can support broader digital transformation. as some customers move away from internally developed systems towards scalable enterprise-grade platforms that can support broader digital transformation Finally, from a revenue category perspective, platform as an application represents approximately 40% of digital revenue, followed by professional services, digital operations and digital exploration. finally from a revenue category perspective platform as an application represents approximately 40% of digital revenue followed by professional services digital operations and digital exploration That mix will evolve as digital operations continue to scale. that mix will evolve as digital operations continue to scale We expect it to become the largest part of the business over time, as I will describe momentarily. we expect it to become the largest part of the business over time as i will describe momentarily Overall, this is a well-balanced business. It is not dependent on one geography, one customer or one product line. It is also supported by the breadth of the broader SLB portfolio and our global reach. Taken together, that gives us confidence in both the durability of the business and the opportunity ahead. Next, building on what Rakesh outlined earlier, let me turn to the market opportunity and where we see the strongest growth. Recent third-party analysis shows the total addressable market for our digital business growing to approximately $35 billion by 2030. That view aligns closely with SLB's internal analysis. When we map the market by category, we expect the strongest growth to come from digital operations, where the market is expected to grow at an 11% CAGR through 2030. Overall, this is a well-balanced business. overall this is a well-balanced business It is not dependent on one geography, one customer or one product line. it is not dependent on one geography one customer or one product line It is also supported by the breadth of the broader SLB portfolio and our global reach. it is also supported by the breadth of the broader slb portfolio and our global reach Taken together, that gives us confidence in both the durability of the business and the opportunity ahead. taken together that gives us confidence in both the durability of the business and the opportunity ahead Next, building on what Rakesh outlined earlier, let me turn to the market opportunity and where we see the strongest growth. next building on what rakesh outlined earlier let me turn to the market opportunity and where we see the strongest growth Recent third-party analysis shows the total addressable market for our digital business growing to approximately $35 billion by 2030. recent third-party analysis shows the total addressable market for our digital business growing to approximately $35 billion by 2030 That view aligns closely with SLB's internal analysis. that view aligns closely with slb's internal analysis When we map the market by category, we expect the strongest growth to come from digital operations, where the market is expected to grow at an 11% CAGR through 2030. when we map the market by category we expect the strongest growth to come from digital operations where the market is expected to grow at an 11% cagr through 2030 This is compared with about 8% for the overall digital market. As I highlighted earlier this morning, there is meaningful upside to this outlook. If adoption of AI solution moves faster than currently forecasted, the digital market could expand to as much as $50 billion by 2030, representing a 15% CAGR. Together these trends, along with our differentiated market position, give us confidence that we can grow digital revenue at a 10%-15% CAGR through the end of the decade. With the higher end of this range based on accelerated AI adoption. This revenue trajectory would outpace both oil and gas upstream investment, as well as the industry's digital spend, as we believe we can leverage our digital platforms, customer footprints and AI capabilities to continue growing ahead of the market. This is compared with about 8% for the overall digital market. this is compared with about 8% for the overall digital market As I highlighted earlier this morning, there is meaningful upside to this outlook. as i highlighted earlier this morning there is meaningful upside to this outlook If adoption of AI solution moves faster than currently forecasted, the digital market could expand to as much as $50 billion by 2030, representing a 15% CAGR. if adoption of ai solution moves faster than currently forecasted the digital market could expand to as much as $50 billion by 2030 representing a 15% cagr Together these trends, along with our differentiated market position, give us confidence that we can grow digital revenue at a 10%-15% CAGR through the end of the decade. together these trends along with our differentiated market position give us confidence that we can grow digital revenue at a 10%-15% cagr through the end of the decade With the higher end of this range based on accelerated AI adoption. with the higher end of this range based on accelerated ai adoption This revenue trajectory would outpace both oil and gas upstream investment, as well as the industry's digital spend, as we believe we can leverage our digital platforms, customer footprints and AI capabilities to continue growing ahead of the market. this revenue trajectory would outpace both oil and gas upstream investment as well as the industry's digital spend as we believe we can leverage our digital platforms customer footprints and ai capabilities to continue growing ahead of the market Notably, we expect to deliver this level of revenue growth without significant M&A activity, although we will continue to consider bolt-on technology acquisition that can further strengthen our offering. With that as the backdrop, let me now turn to how we will monetize that opportunity. Our digital offerings are monetized through several commercial models, each contributing differently to growth, margins, and recurring revenue. Platforms and applications are largely recurring. They are sold through software subscriptions or perpetual licenses with annual maintenance. Digital operations has a different model. It is generally sold as an incremental digital line item connected to our core services or equipment. Revenue in this category is repeatable or sometimes recurring, and typically delivers high incremental margins. Digital exploration represents our exploration data business, which consists of a differentiated library of seismic surveys and other subsurface data covering key basins worldwide. Notably, we expect to deliver this level of revenue growth without significant M&A activity, although we will continue to consider bolt-on technology acquisition that can further strengthen our offering. notably we expect to deliver this level of revenue growth without significant m&a activity although we will continue to consider bolt-on technology acquisition that can further strengthen our offering With that as the backdrop, let me now turn to how we will monetize that opportunity. with that as the backdrop let me now turn to how we will monetize that opportunity Our digital offerings are monetized through several commercial models, each contributing differently to growth, margins, and recurring revenue. our digital offerings are monetized through several commercial models each contributing differently to growth margins and recurring revenue Platforms and applications are largely recurring. platforms and applications are largely recurring They are sold through software subscriptions or perpetual licenses with annual maintenance. they are sold through software subscriptions or perpetual licenses with annual maintenance Digital operations has a different model. digital operations has a different model It is generally sold as an incremental digital line item connected to our core services or equipment. it is generally sold as an incremental digital line item connected to our core services or equipment Revenue in this category is repeatable or sometimes recurring, and typically delivers high incremental margins. revenue in this category is repeatable or sometimes recurring and typically delivers high incremental margins Digital exploration represents our exploration data business, which consists of a differentiated library of seismic surveys and other subsurface data covering key basins worldwide. digital exploration represents our exploration data business which consists of a differentiated library of seismic surveys and other subsurface data covering key basins worldwide This is usually highly profitable but non-recurring in nature, with revenue generated primarily through one-time license sales. Our success in producing and selling high-quality data is highly dependent on the use of our platforms and applications, enhanced by our domain foundation models. Finally, professional services is more project-based. It includes consulting and technology services required to support our clients' digital transformations. Although this category has lower relative profitability than the other digital categories, it remains strategically important because it helps drive adoption and creates pull-through across the broader portfolio. In short, we have multiple ways to monetize the digital opportunity. More importantly, these various models reinforce one another, and combined, they create a business with growth, resilience, and flexibility. This is usually highly profitable but non-recurring in nature, with revenue generated primarily through one-time license sales. this is usually highly profitable but non-recurring in nature with revenue generated primarily through one-time license sales Our success in producing and selling high-quality data is highly dependent on the use of our platforms and applications, enhanced by our domain foundation models. our success in producing and selling high-quality data is highly dependent on the use of our platforms and applications enhanced by our domain foundation models Finally, professional services is more project-based. finally professional services is more project-based It includes consulting and technology services required to support our clients' digital transformations. it includes consulting and technology services required to support our clients' digital transformations Although this category has lower relative profitability than the other digital categories, it remains strategically important because it helps drive adoption and creates pull-through across the broader portfolio. although this category has lower relative profitability than the other digital categories it remains strategically important because it helps drive adoption and creates pull-through across the broader portfolio In short, we have multiple ways to monetize the digital opportunity. in short we have multiple ways to monetize the digital opportunity More importantly, these various models reinforce one another, and combined, they create a business with growth, resilience, and flexibility. more importantly these various models reinforce one another and combined they create a business with growth resilience and flexibility Let me now go 1 level deeper into the 2 areas with the strongest growth potential, namely platforms and applications and digital operations, and explain how we will unlock further growth and value. In platforms and applications, we see 3 key levers for increasing monetization. First, gradually transitioning on-premises customers from perpetual licenses with maintenance to subscription models. This allows for better tiering of our commercial offering based on the features our customers choose to consume. Second, migrating more customers from on-premises offerings to the cloud. Third, monetizing consumption across the portfolio as customers expand usage of our platforms and applications, data environment, and AI solutions. As you can see, growth in platforms and applications is not only about adding customers. It is also about shifting the mix towards more recurring subscription and consumption or outcome-based models. Let me now go 1 level deeper into the 2 areas with the strongest growth potential, namely platforms and applications and digital operations, and explain how we will unlock further growth and value. let me now go 1 level deeper into the 2 areas with the strongest growth potential namely platforms and applications and digital operations and explain how we will unlock further growth and value In platforms and applications, we see 3 key levers for increasing monetization. in platforms and applications we see 3 key levers for increasing monetization First, gradually transitioning on-premises customers from perpetual licenses with maintenance to subscription models. first gradually transitioning on-premises customers from perpetual licenses with maintenance to subscription models This allows for better tiering of our commercial offering based on the features our customers choose to consume. this allows for better tiering of our commercial offering based on the features our customers choose to consume Second, migrating more customers from on-premises offerings to the cloud. second migrating more customers from on-premises offerings to the cloud Third, monetizing consumption across the portfolio as customers expand usage of our platforms and applications, data environment, and AI solutions. third monetizing consumption across the portfolio as customers expand usage of our platforms and applications data environment and ai solutions As you can see, growth in platforms and applications is not only about adding customers. as you can see growth in platforms and applications is not only about adding customers It is also about shifting the mix towards more recurring subscription and consumption or outcome-based models. it is also about shifting the mix towards more recurring subscription and consumption or outcome-based models This will improve revenue predictability, reduce sales volatility, increase contract lifetime value, and improve customer retention. The opportunity in digital operations is of a different nature and scale. Here, we believe we can increase the size of the market, if not create the market, by scaling connected equipment and autonomous workflows across customer operations with new AI capabilities further accelerating that trend. Today, those digital services only represent about 1.5% of our core equipment and services revenue, despite delivering significant results in the field. As customers increasingly recognize the benefits of these solutions, we see the potential for spending in this category to grow at an elevated rate, potentially tripling by 2030, supported by digital add-ons and increased outcome-based pricing. Taken together, the evolution of platforms and applications and digital operations are expected to drive a majority of the growth in our digital business. This will improve revenue predictability, reduce sales volatility, increase contract lifetime value, and improve customer retention. this will improve revenue predictability reduce sales volatility increase contract lifetime value and improve customer retention The opportunity in digital operations is of a different nature and scale. the opportunity in digital operations is of a different nature and scale Here, we believe we can increase the size of the market, if not create the market, by scaling connected equipment and autonomous workflows across customer operations with new AI capabilities further accelerating that trend. here we believe we can increase the size of the market if not create the market by scaling connected equipment and autonomous workflows across customer operations with new ai capabilities further accelerating that trend Today, those digital services only represent about 1.5% of our core equipment and services revenue, despite delivering significant results in the field. today those digital services only represent about 1.5% of our core equipment and services revenue despite delivering significant results in the field As customers increasingly recognize the benefits of these solutions, we see the potential for spending in this category to grow at an elevated rate, potentially tripling by 2030, supported by digital add-ons and increased outcome-based pricing. as customers increasingly recognize the benefits of these solutions we see the potential for spending in this category to grow at an elevated rate potentially tripling by 2030 supported by digital add-ons and increased outcome-based pricing Taken together, the evolution of platforms and applications and digital operations are expected to drive a majority of the growth in our digital business. taken together the evolution of platforms and applications and digital operations are expected to drive a majority of the growth in our digital business The value generated from these offerings will continue to compound. As platform usage increases, more data is organized and activated. As more assets and operations become connected, the opportunity to automate workflows expands. As AI becomes embedded in those workflows, the value we create for customer increases. All in all, this will support our ability to continue delivering attractive digital growth with margins that are highly accretive to SLB. To make this more explicit, let me now close by sharing our 2030 financial ambitions. Based on market growth and the trends we are seeing in terms of adoption and monetization, we expect to double digital annual recurring revenue to approximately $2 billion by 2030. This is supported by the assumption I shared earlier that digital revenue will grow at a 10%-15% CAGR from 2025 through 2030. The value generated from these offerings will continue to compound. the value generated from these offerings will continue to compound As platform usage increases, more data is organized and activated. as platform usage increases more data is organized and activated As more assets and operations become connected, the opportunity to automate workflows expands. as more assets and operations become connected the opportunity to automate workflows expands As AI becomes embedded in those workflows, the value we create for customer increases. as ai becomes embedded in those workflows the value we create for customer increases All in all, this will support our ability to continue delivering attractive digital growth with margins that are highly accretive to SLB. all in all this will support our ability to continue delivering attractive digital growth with margins that are highly accretive to slb To make this more explicit, let me now close by sharing our 2030 financial ambitions. to make this more explicit let me now close by sharing our 2030 financial ambitions Based on market growth and the trends we are seeing in terms of adoption and monetization, we expect to double digital annual recurring revenue to approximately $2 billion by 2030. based on market growth and the trends we are seeing in terms of adoption and monetization we expect to double digital annual recurring revenue to approximately $2 billion by 2030 This is supported by the assumption I shared earlier that digital revenue will grow at a 10%-15% CAGR from 2025 through 2030. this is supported by the assumption i shared earlier that digital revenue will grow at a 10%-15% cagr from 2025 through 2030 We also see a path to approximately double our current adjusted EBITDA for digital to between $1.8 billion and $2 billion by 2030. With margins expanding to a range of 38%-42% towards the end of the decade. Our ability to achieve margins towards the higher end of this range will depend on our success in increasing the share of subscription-based revenue in our mix, the continued expansion of digital operations, and the addition of AI-driven capabilities that create incremental value for customers and support better monetization of the outcomes we help enable. In summary, digital is already helping to accelerate SLB's growth with accretive margins and compelling returns. As adoption continues to expand across platforms, operations, data, and AI, we see a clear path to sustained double-digit growth, continued margin expansion, and increasing contribution to SLB's overall returns over time. Thank you for your attention. We also see a path to approximately double our current adjusted EBITDA for digital to between $1.8 billion and $2 billion by 2030. we also see a path to approximately double our current adjusted ebitda for digital to between $1.8 billion and $2 billion by 2030 With margins expanding to a range of 38%-42% towards the end of the decade. with margins expanding to a range of 38%-42% towards the end of the decade Our ability to achieve margins towards the higher end of this range will depend on our success in increasing the share of subscription-based revenue in our mix, the continued expansion of digital operations, and the addition of AI-driven capabilities that create incremental value for customers and support better monetization of the outcomes we help enable. our ability to achieve margins towards the higher end of this range will depend on our success in increasing the share of subscription-based revenue in our mix the continued expansion of digital operations and the addition of ai-driven capabilities that create incremental value for customers and support better monetization of the outcomes we help enable In summary, digital is already helping to accelerate SLB's growth with accretive margins and compelling returns. in summary digital is already helping to accelerate slb's growth with accretive margins and compelling returns As adoption continues to expand across platforms, operations, data, and AI, we see a clear path to sustained double-digit growth, continued margin expansion, and increasing contribution to SLB's overall returns over time. as adoption continues to expand across platforms operations data and ai we see a clear path to sustained double-digit growth continued margin expansion and increasing contribution to slb's overall returns over time Thank you for your attention. thank you for your attention I will now turn it back to Olivier. I will now turn it back to Olivier. i will now turn it back to olivier

Speaker 13: Thank you, Stéphane. Ladies and gentlemen, as we conclude, let me leave you with this. Digital is becoming central to how this industry plans, operates, and creates value. What you have heard today reflects a leading position SLB has built over many years. It is one that is powered by science, accelerated by AI, and built for the complexity of energy operations. We are the only company that brings together the domain expertise, the technology, the partnerships, and global execution to redefine what is possible where it matters most. This is just the beginning. In the age of artificial intelligence, new opportunities are being unlocked across all industries, and we are pursuing them not only through the digital frame we discussed today, but also through our data center solution business. Thank you, Stéphane. thank you stéphane Ladies and gentlemen, as we conclude, let me leave you with this. ladies and gentlemen as we conclude let me leave you with this Digital is becoming central to how this industry plans, operates, and creates value. digital is becoming central to how this industry plans operates and creates value What you have heard today reflects a leading position SLB has built over many years. what you have heard today reflects a leading position slb has built over many years It is one that is powered by science, accelerated by AI, and built for the complexity of energy operations. it is one that is powered by science accelerated by ai and built for the complexity of energy operations We are the only company that brings together the domain expertise, the technology, the partnerships, and global execution to redefine what is possible where it matters most. we are the only company that brings together the domain expertise the technology the partnerships and global execution to redefine what is possible where it matters most This is just the beginning. this is just the beginning In the age of artificial intelligence, new opportunities are being unlocked across all industries, and we are pursuing them not only through the digital frame we discussed today, but also through our data center solution business. in the age of artificial intelligence new opportunities are being unlocked across all industries and we are pursuing them not only through the digital frame we discussed today but also through our data center solution business There, we are extending our work with hyperscalers, the same partners we work with and collaborate in our digital upstream business to deliver the physical infrastructure required to scale AI. In that sense, SLB is uniquely positioned to benefit from the secular growth of AI in two ways: through the platform and digital solutions that transform energy operations and through the infrastructure that enables AI to scale. If there is one takeaway, it is this: Our digital leadership is real, it is differentiated, and it is creating long-term value for SLB and its shareholders. Thank you for joining us today and for your engagement throughout the session. With that, I would like to invite today's speakers to come with me on stage for the Q&A session. There, we are extending our work with hyperscalers, the same partners we work with and collaborate in our digital upstream business to deliver the physical infrastructure required to scale AI. there we are extending our work with hyperscalers the same partners we work with and collaborate in our digital upstream business to deliver the physical infrastructure required to scale ai In that sense, SLB is uniquely positioned to benefit from the secular growth of AI in two ways: through the platform and digital solutions that transform energy operations and through the infrastructure that enables AI to scale. in that sense slb is uniquely positioned to benefit from the secular growth of ai in two ways through the platform and digital solutions that transform energy operations and through the infrastructure that enables ai to scale If there is one takeaway, it is this: Our digital leadership is real, it is differentiated, and it is creating long-term value for SLB and its shareholders. if there is one takeaway it is this our digital leadership is real it is differentiated and it is creating long-term value for slb and its shareholders Thank you for joining us today and for your engagement throughout the session. thank you for joining us today and for your engagement throughout the session With that, I would like to invite today's speakers to come with me on stage for the Q&A session. with that i would like to invite today's speakers to come with me on stage for the q&a session

Speaker 8: Thank you again for your attendance. It is now my pleasure to open it up to questions. If you have a question, please raise your hand and we will come to you with a microphone. Please introduce yourselves and ask only one question so that we can get to as many of you as possible. As you're thinking about your question, allow me to kick it off by asking Olivier about something we've been hearing a lot lately. Olivier, as we think about SLB's digital next phase, what gives you the confidence that this business can evolve into a scaled higher multiple engine, distinct from traditional oil field services, and what proof points should investors focus on today? Thank you again for your attendance. thank you again for your attendance It is now my pleasure to open it up to questions. it is now my pleasure to open it up to questions If you have a question, please raise your hand and we will come to you with a microphone. if you have a question please raise your hand and we will come to you with a microphone Please introduce yourselves and ask only one question so that we can get to as many of you as possible. please introduce yourselves and ask only one question so that we can get to as many of you as possible As you're thinking about your question, allow me to kick it off by asking Olivier about something we've been hearing a lot lately. as you're thinking about your question allow me to kick it off by asking olivier about something we've been hearing a lot lately Olivier, as we think about SLB's digital next phase, what gives you the confidence that this business can evolve into a scaled higher multiple engine, distinct from traditional oil field services, and what proof points should investors focus on today? olivier as we think about slb's digital next phase what gives you the confidence that this business can evolve into a scaled higher multiple engine distinct from traditional oil field services and what proof points should investors focus on today

Speaker 13: Thank you, James. Indeed, I think I would state first thing is that we are not building our digital capability anymore. We have built it. We're here to scale it. If you look at the proof point of where we stand today, we are already going at double digit with expanding margins, and we are seeing a mix further evolving towards increased recurring and consumption-based revenue. What makes me confident is that we have a clear path forward. The clear path forward is resilient on digital operation and AI solution. The sandbox is a total SLB OFE footprint. That is unique. The capability we have together, the domain, the platform, including AI-ready stack, the partnership ecosystem we have developed, and the global reach, as we said, is unique. When you combine all of this, as we continue to scale, the ARR will shift upwards. Thank you, James. thank you james Indeed, I think I would state first thing is that we are not building our digital capability anymore. indeed i think i would state first thing is that we are not building our digital capability anymore We have built it. we have built it We're here to scale it. we're here to scale it If you look at the proof point of where we stand today, we are already going at double digit with expanding margins, and we are seeing a mix further evolving towards increased recurring and consumption-based revenue. if you look at the proof point of where we stand today we are already going at double digit with expanding margins and we are seeing a mix further evolving towards increased recurring and consumption-based revenue What makes me confident is that we have a clear path forward. what makes me confident is that we have a clear path forward The clear path forward is resilient on digital operation and AI solution. the clear path forward is resilient on digital operation and ai solution The sandbox is a total SLB OFE footprint. the sandbox is a total slb ofe footprint That is unique. that is unique The capability we have together, the domain, the platform, including AI-ready stack, the partnership ecosystem we have developed, and the global reach, as we said, is unique. the capability we have together the domain the platform including ai-ready stack the partnership ecosystem we have developed and the global reach as we said is unique When you combine all of this, as we continue to scale, the ARR will shift upwards. when you combine all of this as we continue to scale the arr will shift upwards The consumption base on our platform will start to be clear, and our margins will resemble software-like margins. When you put all this together, I believe this will deserve a higher multiple. I think it's no more physical growth. It is durable growth that will compound and create value for the company. The consumption base on our platform will start to be clear, and our margins will resemble software-like margins. the consumption base on our platform will start to be clear and our margins will resemble software-like margins When you put all this together, I believe this will deserve a higher multiple. when you put all this together i believe this will deserve a higher multiple I think it's no more physical growth. i think it's no more physical growth It is durable growth that will compound and create value for the company. it is durable growth that will compound and create value for the company

Speaker 8: Thank you, Olivier. Let's take questions now from the audience. We have one right up here up front. Thank you, Olivier. thank you olivier Let's take questions now from the audience. let's take questions now from the audience We have one right up here up front. we have one right up here up front

Speaker 11: Hey, thank you. Marc Bianchi with TD Cowen. Thank you for the presentation. I'm curious to achieve these targets, I think you talked about $3 billion of R&D spend since 2016. Can you talk about what additional R&D spend is contemplated to get to these targets? Related to that, how do you see this initiative sort of helping the capital intensity of the overall business? Do we see a reduction in capital per dollar of revenue, for instance, as time goes on and you're able to implement more of these capabilities? Hey, thank you. hey thank you Marc Bianchi with TD Cowen. marc bianchi with td cowen Thank you for the presentation. thank you for the presentation I'm curious to achieve these targets, I think you talked about $3 billion of R&D spend since 2016. i'm curious to achieve these targets i think you talked about $3 billion of r&d spend since 2016 Can you talk about what additional R&D spend is contemplated to get to these targets? can you talk about what additional r&d spend is contemplated to get to these targets Related to that, how do you see this initiative sort of helping the capital intensity of the overall business? related to that how do you see this initiative sort of helping the capital intensity of the overall business Do we see a reduction in capital per dollar of revenue, for instance, as time goes on and you're able to implement more of these capabilities? do we see a reduction in capital per dollar of revenue for instance as time goes on and you're able to implement more of these capabilities

Speaker 8: Thank you, Marc, for the question. Stéphane, can I pass that one to you? Thank you, Marc, for the question. thank you marc for the question Stéphane, can I pass that one to you? stéphane can i pass that one to you

Speaker 21: Yes, of course. Thank you, Marc. Look, as Olivier mentioned, the foundations are built. We've spent actually decades and increased R&D in the last few years to get there. We are not going to stop there. We will always need to enrich the platform. In terms of R&D, you've seen the numbers over the last 10 years. I would expect this, of course, not to increase as fast as the revenue, if it ever increases. You will gain operating leverage from this, but we will continue to enhance the platform and invest into it. Yes, of course. yes of course Thank you, Marc. thank you marc Look, as Olivier mentioned, the foundations are built. look as olivier mentioned the foundations are built We've spent actually decades and increased R&D in the last few years to get there. we've spent actually decades and increased r&d in the last few years to get there We are not going to stop there. we are not going to stop there We will always need to enrich the platform. we will always need to enrich the platform In terms of R&D, you've seen the numbers over the last 10 years. in terms of r&d you've seen the numbers over the last 10 years I would expect this, of course, not to increase as fast as the revenue, if it ever increases. i would expect this of course not to increase as fast as the revenue if it ever increases You will gain operating leverage from this, but we will continue to enhance the platform and invest into it. you will gain operating leverage from this but we will continue to enhance the platform and invest into it

Speaker 8: I have a question right here in the middle. Scott? I have a question right here in the middle. i have a question right here in the middle Scott? scott

Speaker 17: Yes. Scott Gruber from Citigroup. Thanks for the presentation this morning. Super impressive. I'm curious about the pricing strategy for some of these services. Thinking back to the digital operations examples where autonomous drilling can save 25%-40% on the drilling time of a well. If you think about that in the context of a deep water well, it could be like $25 million. Which is a huge amount of savings. How do you guys think about what is the fair share of that savings for Schlumberger, SLB, sorry, I'm old school, for SLB to capture versus how much you share with the client? Obviously, you want to push the adoption of these services and scale it up, but there's a huge amount of value creation there. How do you think about the pricing strategy with that value creation potential? Yes. yes Scott Gruber from Citigroup. scott gruber from citigroup Thanks for the presentation this morning. thanks for the presentation this morning Super impressive. super impressive I'm curious about the pricing strategy for some of these services. i'm curious about the pricing strategy for some of these services Thinking back to the digital operations examples where autonomous drilling can save 25%-40% on the drilling time of a well. thinking back to the digital operations examples where autonomous drilling can save 25%-40% on the drilling time of a well If you think about that in the context of a deep water well, it could be like $25 million. if you think about that in the context of a deep water well it could be like $25 million Which is a huge amount of savings. which is a huge amount of savings How do you guys think about what is the fair share of that savings for Schlumberger, SLB, sorry, I'm old school, for SLB to capture versus how much you share with the client? how do you guys think about what is the fair share of that savings for schlumberger slb sorry i'm old school for slb to capture versus how much you share with the client Obviously, you want to push the adoption of these services and scale it up, but there's a huge amount of value creation there. obviously you want to push the adoption of these services and scale it up but there's a huge amount of value creation there How do you think about the pricing strategy with that value creation potential? how do you think about the pricing strategy with that value creation potential

Speaker 8: Rakesh, would you like to kick off that question and perhaps, Cecilia, on digital operations, you can have a follow-up? Rakesh, would you like to kick off that question and perhaps, Cecilia, on digital operations, you can have a follow-up? rakesh would you like to kick off that question and perhaps cecilia on digital operations you can have a follow-up

Speaker 15: Thank you. I think for different categories of revenue, as we've reported, the pricing strategies, of course, vary. For the operations, as you rightly point out, significant value for our customers, and we will therefore be in a very strong position to be able to scale. In the operations, as I think Stéphane briefly mentioned, we are talking about almost very little new investment for us to be able to provide this value addition because of the fact that we are utilizing the existing hardware already, and we are just bringing new algorithms to be able to bring the value for our customers. Thank you. thank you I think for different categories of revenue, as we've reported, the pricing strategies, of course, vary. i think for different categories of revenue as we've reported the pricing strategies of course vary For the operations, as you rightly point out, significant value for our customers, and we will therefore be in a very strong position to be able to scale. for the operations as you rightly point out significant value for our customers and we will therefore be in a very strong position to be able to scale In the operations, as I think Stéphane briefly mentioned, we are talking about almost very little new investment for us to be able to provide this value addition because of the fact that we are utilizing the existing hardware already, and we are just bringing new algorithms to be able to bring the value for our customers. in the operations as i think stéphane briefly mentioned we are talking about almost very little new investment for us to be able to provide this value addition because of the fact that we are utilizing the existing hardware already and we are just bringing new algorithms to be able to bring the value for our customers Of course, we expect, therefore, the margins to be very, very significantly accretive, as I think mentioned by Stéphane. For the other categories, for example, in the platforms and applications, again, I think the fact that we have a very distinctive and a very strong offering, we expect to scale that. Therefore, the additional scaling would not cost us very much, which is why the confidence that we have in terms of even stronger margins in the years ahead. Then, of course, the agentic AI, that will bring significant value on top of what we are already charging, and that should bring significant margins for us going forward as well. If I look at those, each one of those categories has distinct advantages, which will continue to bring more margins for us going forward. Of course, we expect, therefore, the margins to be very, very significantly accretive, as I think mentioned by Stéphane. of course we expect therefore the margins to be very very significantly accretive as i think mentioned by stéphane For the other categories, for example, in the platforms and applications, again, I think the fact that we have a very distinctive and a very strong offering, we expect to scale that. for the other categories for example in the platforms and applications again i think the fact that we have a very distinctive and a very strong offering we expect to scale that Therefore, the additional scaling would not cost us very much, which is why the confidence that we have in terms of even stronger margins in the years ahead. therefore the additional scaling would not cost us very much which is why the confidence that we have in terms of even stronger margins in the years ahead Then, of course, the agentic AI, that will bring significant value on top of what we are already charging, and that should bring significant margins for us going forward as well. then of course the agentic ai that will bring significant value on top of what we are already charging and that should bring significant margins for us going forward as well If I look at those, each one of those categories has distinct advantages, which will continue to bring more margins for us going forward. if i look at those each one of those categories has distinct advantages which will continue to bring more margins for us going forward

Speaker 8: Cecilia, perhaps you want to elaborate on operations? Cecilia, perhaps you want to elaborate on operations? cecilia perhaps you want to elaborate on operations

Speaker 3: A couple of points other than what Rakesh has said. First of all, many and most of our contracts are performance-based contracts. When we get this additional digital add-on service, we actually increase revenue not just from digital, but also from our general operations. Second is many of our digital operations that we sell actually are agnostic. As in the completions example, when we merge the digital piece with our innovative hardware, that's when we see a step change in performance. It is also an enabler to bring additional pull-through revenue for the locations where we're not having operations there. A couple of points other than what Rakesh has said. a couple of points other than what rakesh has said First of all, many and most of our contracts are performance-based contracts. first of all many and most of our contracts are performance-based contracts When we get this additional digital add-on service, we actually increase revenue not just from digital, but also from our general operations. when we get this additional digital add-on service we actually increase revenue not just from digital but also from our general operations Second is many of our digital operations that we sell actually are agnostic. second is many of our digital operations that we sell actually are agnostic As in the completions example, when we merge the digital piece with our innovative hardware, that's when we see a step change in performance. as in the completions example when we merge the digital piece with our innovative hardware that's when we see a step change in performance It is also an enabler to bring additional pull-through revenue for the locations where we're not having operations there. it is also an enabler to bring additional pull-through revenue for the locations where we're not having operations there

Speaker 8: Thank you, Cecilia. James. See you right here. Thank you, Cecilia. thank you cecilia James. james See you right here. see you right here

Speaker 31: Not James, yeah. Not James, yeah. not james yeah

Speaker 8: Yeah. Yeah. yeah Sorry. James, question about the changing dynamics that we've seen, how it impacts the digital adoption in this space. Energy and power has changed a lot in the last 110 days. Of course, that change with energy security started in 2022 as well but has become more pronounced. Olivier, you're having a CEO to CEO conversation, and I'm curious what the feedback is from the customer base about the security of their operations as they move more and more information to the cloud and go more digital. Do they worry about cybersecurity? Do they worry about hacks, things like that? Does that limit, or have you created a platform where they're very comfortable that you can protect their data? Sorry. sorry James, question about the changing dynamics that we've seen, how it impacts the digital adoption in this space. james question about the changing dynamics that we've seen how it impacts the digital adoption in this space Energy and power has changed a lot in the last 110 days. energy and power has changed a lot in the last 110 days Of course, that change with energy security started in 2022 as well but has become more pronounced. of course that change with energy security started in 2022 as well but has become more pronounced Olivier, you're having a CEO to CEO conversation, and I'm curious what the feedback is from the customer base about the security of their operations as they move more and more information to the cloud and go more digital. olivier you're having a ceo to ceo conversation and i'm curious what the feedback is from the customer base about the security of their operations as they move more and more information to the cloud and go more digital Do they worry about cybersecurity? do they worry about cybersecurity Do they worry about hacks, things like that? do they worry about hacks things like that Does that limit, or have you created a platform where they're very comfortable that you can protect their data? does that limit or have you created a platform where they're very comfortable that you can protect their data Olivier, would you like to take the first part of the question, then perhaps we can pass it to Shashi for the second part? Olivier, would you like to take the first part of the question, then perhaps we can pass it to Shashi for the second part? olivier would you like to take the first part of the question then perhaps we can pass it to shashi for the second part

Speaker 13: Yeah. The first thing I would say is, Canon, that what is happening today with energy security, the need for supply diversification, the need to secure and accelerate supply management is all playing to the strengths of the impact of digital in our industry. Anything I'm hearing from customers, the same way we heard back in 2020, is that digital is becoming more critical and more essential to unlock the performance efficiency to fast-track the cycle of first oil, first gas, and to improve recovery for the market, for the assets that can be deployed securely in the world. This is the trend that we see is only accelerating, is a secular trend that we believe that this crisis is only reinforcing. The role of digital going forward will be a shift and a critical transition for the industry. Yeah. yeah The first thing I would say is, Canon, that what is happening today with energy security, the need for supply diversification, the need to secure and accelerate supply management is all playing to the strengths of the impact of digital in our industry. the first thing i would say is canon that what is happening today with energy security the need for supply diversification the need to secure and accelerate supply management is all playing to the strengths of the impact of digital in our industry Anything I'm hearing from customers, the same way we heard back in 2020, is that digital is becoming more critical and more essential to unlock the performance efficiency to fast-track the cycle of first oil, first gas, and to improve recovery for the market, for the assets that can be deployed securely in the world. anything i'm hearing from customers the same way we heard back in 2020 is that digital is becoming more critical and more essential to unlock the performance efficiency to fast-track the cycle of first oil first gas and to improve recovery for the market for the assets that can be deployed securely in the world This is the trend that we see is only accelerating, is a secular trend that we believe that this crisis is only reinforcing. this is the trend that we see is only accelerating is a secular trend that we believe that this crisis is only reinforcing The role of digital going forward will be a shift and a critical transition for the industry. the role of digital going forward will be a shift and a critical transition for the industry That is happening, and I think this is only accelerating. That's the feedback we're getting, and we are seeing it in adoption. We are seeing the pilots. If any mention of the impact, actually, our digital business in the Middle East has been extremely resilient against this backdrop of crisis. That is happening, and I think this is only accelerating. that is happening and i think this is only accelerating That's the feedback we're getting, and we are seeing it in adoption. that's the feedback we're getting and we are seeing it in adoption We are seeing the pilots. we are seeing the pilots If any mention of the impact, actually, our digital business in the Middle East has been extremely resilient against this backdrop of crisis. if any mention of the impact actually our digital business in the middle east has been extremely resilient against this backdrop of crisis

Speaker 19: Let me add two points here. I think when we talk about customers and their concerns around their assets, I would put them into one aspect, which is around data. We implemented our digital platforms in a way that we can meet the customers where they are. For those customers that are comfortable with a traditional SaaS offering, great, we support all the three hyperscalers. There are customers for whom we have implemented what we call private SaaS, which means deployed solutions onto their tenant, which means it is managed by their own IT and security organization. That's one facet. Of course, there is a set of customers that want everything on-prem. We cover that entire spectrum to say wherever the customer is and their data are, we can deliver a solution there. Let me add two points here. let me add two points here I think when we talk about customers and their concerns around their assets, I would put them into one aspect, which is around data. i think when we talk about customers and their concerns around their assets i would put them into one aspect which is around data We implemented our digital platforms in a way that we can meet the customers where they are. we implemented our digital platforms in a way that we can meet the customers where they are For those customers that are comfortable with a traditional SaaS offering, great, we support all the three hyperscalers. for those customers that are comfortable with a traditional saas offering great we support all the three hyperscalers There are customers for whom we have implemented what we call private SaaS, which means deployed solutions onto their tenant, which means it is managed by their own IT and security organization. there are customers for whom we have implemented what we call private saas which means deployed solutions onto their tenant which means it is managed by their own it and security organization That's one facet. that's one facet Of course, there is a set of customers that want everything on-prem. of course there is a set of customers that want everything on-prem We cover that entire spectrum to say wherever the customer is and their data are, we can deliver a solution there. we cover that entire spectrum to say wherever the customer is and their data are we can deliver a solution there The second angle I would say is from a cybersecurity point of view. We run one of the largest cybersec ops operations across the industry, and we work very closely with leading hyperscalers, plus also security companies like Palo Alto Networks, et cetera, on those, right? We are adopting and using the latest frontier models to test to validate our implementations or any kind of loopholes that might be existing. Then, of course, we work very hand in hand with the customer's own IT and security organizations as well. At the end of the day, for our customers to use our stack, they need to be comfortable that the implementations that we have meet their standards, and that's what we go with. The second angle I would say is from a cybersecurity point of view. the second angle i would say is from a cybersecurity point of view We run one of the largest cybersec ops operations across the industry, and we work very closely with leading hyperscalers, plus also security companies like Palo Alto Networks, et cetera, on those, right? we run one of the largest cybersec ops operations across the industry and we work very closely with leading hyperscalers plus also security companies like palo alto networks et cetera on those right We are adopting and using the latest frontier models to test to validate our implementations or any kind of loopholes that might be existing. we are adopting and using the latest frontier models to test to validate our implementations or any kind of loopholes that might be existing Then, of course, we work very hand in hand with the customer's own IT and security organizations as well. then of course we work very hand in hand with the customer's own it and security organizations as well At the end of the day, for our customers to use our stack, they need to be comfortable that the implementations that we have meet their standards, and that's what we go with. at the end of the day for our customers to use our stack they need to be comfortable that the implementations that we have meet their standards and that's what we go with

Speaker 8: Thank you, Shashi. Right here in second row in the middle. Dave, please. Thank you, Shashi. thank you shashi Right here in second row in the middle. right here in second row in the middle Dave, please. dave please

Speaker 4: Thanks. David Anderson, Barclays. Stéphane, just a real quick point of clarification. On your 2030 targets, was that based on the $50 billion TAM or the $35 billion TAM? Thanks. thanks David Anderson, Barclays. david anderson barclays Stéphane, just a real quick point of clarification. stéphane just a real quick point of clarification On your 2030 targets, was that based on the $50 billion TAM or the $35 billion TAM? on your 2030 targets was that based on the $50 billion tam or the $35 billion tam

Speaker 21: Dave, it's a range. This is why we have a range of EBITDA as well. The revenue itself is between 10%-15% CAGR through that period, right? The market overall, if you take the low end of the TAM we've given you, the $35 billion, that would be 8% CAGR. The $50 billion would be 15% CAGR. It's based on the entire range, if you want. Dave, it's a range. dave it's a range This is why we have a range of EBITDA as well. this is why we have a range of ebitda as well The revenue itself is between 10%-15% CAGR through that period, right? the revenue itself is between 10%-15% cagr through that period right The market overall, if you take the low end of the TAM we've given you, the $35 billion, that would be 8% CAGR. the market overall if you take the low end of the tam we've given you the $35 billion that would be 8% cagr The $50 billion would be 15% CAGR. the $50 billion would be 15% cagr It's based on the entire range, if you want. it's based on the entire range if you want

Speaker 4: Got it. Understood. Olivier, SLB has made a big point today about your mode in digital. You're really the only OFS company doing this. You've been doing this longer than anybody. The foundational models, the domain expertise gives you all a head start or a lead in AI. Your customers are also adopting AI. They're adopting agentic AI, all sorts of platforms as well. Where is that line today? Are you concerned about that line moving? In other words, your customers are going to be adopting some of this in-house. You're going to be providing other things, but is there a concern that that line could shift? What is the concern that some of them are going to be start adopting what you're doing? Got it. got it Understood. understood Olivier, SLB has made a big point today about your mode in digital. olivier slb has made a big point today about your mode in digital You're really the only OFS company doing this. you're really the only ofs company doing this You've been doing this longer than anybody. you've been doing this longer than anybody The foundational models, the domain expertise gives you all a head start or a lead in AI. the foundational models the domain expertise gives you all a head start or a lead in ai Your customers are also adopting AI. your customers are also adopting ai They're adopting agentic AI, all sorts of platforms as well. they're adopting agentic ai all sorts of platforms as well Where is that line today? where is that line today Are you concerned about that line moving? are you concerned about that line moving In other words, your customers are going to be adopting some of this in-house. in other words your customers are going to be adopting some of this in-house You're going to be providing other things, but is there a concern that that line could shift? you're going to be providing other things but is there a concern that that line could shift What is the concern that some of them are going to be start adopting what you're doing? what is the concern that some of them are going to be start adopting what you're doing

Speaker 13: As you heard before, we meet our customer where they are in their digital journey. I think if you look back at the history of digital, 30 years ago, most of the reservoir simulators were owned and developed by our customers. Some of the basic interpretation was done the same way. Over time, the emergence of platform, industrial-grade platform, has replaced those developments. Nowadays, some customers are willing to enter the development of AI model, if not development of agentic AI, using models. What we offer is an open platform. We offer Delfi, Lumi, the data and AI open platform, and Tela as agentic agent framework that our customer can use to extend their agent team, connect to their agentic workflow, connect to their third-party applications, and also embed our domain foundation model or retrain our domain foundation model to their own data set. As you heard before, we meet our customer where they are in their digital journey. as you heard before we meet our customer where they are in their digital journey I think if you look back at the history of digital, 30 years ago, most of the reservoir simulators were owned and developed by our customers. i think if you look back at the history of digital 30 years ago most of the reservoir simulators were owned and developed by our customers Some of the basic interpretation was done the same way. some of the basic interpretation was done the same way Over time, the emergence of platform, industrial-grade platform, has replaced those developments. over time the emergence of platform industrial-grade platform has replaced those developments Nowadays, some customers are willing to enter the development of AI model, if not development of agentic AI, using models. nowadays some customers are willing to enter the development of ai model if not development of agentic ai using models What we offer is an open platform. what we offer is an open platform We offer Delfi, Lumi, the data and AI open platform, and Tela as agentic agent framework that our customer can use to extend their agent team, connect to their agentic workflow, connect to their third-party applications, and also embed our domain foundation model or retrain our domain foundation model to their own data set. we offer delfi lumi the data and ai open platform and tela as agentic agent framework that our customer can use to extend their agent team connect to their agentic workflow connect to their third-party applications and also embed our domain foundation model or retrain our domain foundation model to their own data set That's what is happening in a pilot we have with several customers, and they see a huge benefit of doing so because they have a starting base that is a step change from what they can do by themselves. As we said, the relationship with NVIDIA give us the guarantee that you have peak performance on the domain foundation model. We have designed it from the ground up, not using the existing Frontier model. We are designing using our science, our technology from the ground up with the guardrails that you integrate it from NVIDIA, from other provider into it. The starting point is very strong. The framework we have give them the freedom to extend, and that's what is attractive into our offering to the customer today. That's what is happening in a pilot we have with several customers, and they see a huge benefit of doing so because they have a starting base that is a step change from what they can do by themselves. that's what is happening in a pilot we have with several customers and they see a huge benefit of doing so because they have a starting base that is a step change from what they can do by themselves As we said, the relationship with NVIDIA give us the guarantee that you have peak performance on the domain foundation model. as we said the relationship with nvidia give us the guarantee that you have peak performance on the domain foundation model We have designed it from the ground up, not using the existing Frontier model. we have designed it from the ground up not using the existing frontier model We are designing using our science, our technology from the ground up with the guardrails that you integrate it from NVIDIA, from other provider into it. we are designing using our science our technology from the ground up with the guardrails that you integrate it from nvidia from other provider into it The starting point is very strong. the starting point is very strong The framework we have give them the freedom to extend, and that's what is attractive into our offering to the customer today. the framework we have give them the freedom to extend and that's what is attractive into our offering to the customer today

Speaker 8: Yes. Right back here. Right here in the middle. Can someone pass the microphone? Yeah. Yes. yes Right back here. right back here Right here in the middle. right here in the middle Can someone pass the microphone? can someone pass the microphone Yeah. yeah

Speaker 18: Hi there. Sebastian Erskine from Rothschild & Co. Just a question. In one of the presentations, you mentioned about the performance-based contract in Libya, actually trying to buy in a bit to the efficiencies that customers can gain. Obviously, that's interesting to me. When we look at U.S. land, one of the big stories was the deflation services, the fact that E&Ps could do more with less. How much as a % of these performance-based contracts or pricing-based, outcome-based models do you see and a scope for that in digital operations going forward? Thank you. Hi there. hi there Sebastian Erskine from Rothschild & Co. Just a question. sebastian erskine from rothschild & co just a question In one of the presentations, you mentioned about the performance-based contract in Libya, actually trying to buy in a bit to the efficiencies that customers can gain. in one of the presentations you mentioned about the performance-based contract in libya actually trying to buy in a bit to the efficiencies that customers can gain Obviously, that's interesting to me. obviously that's interesting to me When we look at U.S. land, one of the big stories was the deflation services, the fact that E&Ps could do more with less. when we look at u.s land one of the big stories was the deflation services the fact that e&ps could do more with less How much as a % of these performance-based contracts or pricing-based, outcome-based models do you see and a scope for that in digital operations going forward? how much as a % of these performance-based contracts or pricing-based outcome-based models do you see and a scope for that in digital operations going forward Thank you. thank you

Speaker 8: Cecilia, I think you answered part of that question earlier. Cecilia, I think you answered part of that question earlier. cecilia i think you answered part of that question earlier

Speaker 3: Yeah. It's a large % of our contracts are performance-based contracts. I believe you were asking specifically on the U.S. market. In U.S. market, we have a very flexible go-to-market approach. We rent and sell our equipment as well as do the services. Many of our services are performance-based, then the rental and the sale of our equipment is through a third-party competitor. Yeah. yeah It's a large % of our contracts are performance-based contracts. it's a large % of our contracts are performance-based contracts I believe you were asking specifically on the U.S. market. i believe you were asking specifically on the u.s market In U.S. market, we have a very flexible go-to-market approach. in u.s market we have a very flexible go-to-market approach We rent and sell our equipment as well as do the services. we rent and sell our equipment as well as do the services Many of our services are performance-based, then the rental and the sale of our equipment is through a third-party competitor. many of our services are performance-based then the rental and the sale of our equipment is through a third-party competitor

Speaker 8: Yes. Right back here. Yes. yes Right back here. right back here

Speaker 7: Thanks. Heath Terry, Citi. Really appreciate you taking the time on all of this, particularly the level of detail around some of your technology partnerships. The reliance that you have on the cloud providers, they've obviously been very vocal about the issues that they're dealing with from a supply perspective and the constraints with demand increasing the way that it is. That's showing up in pricing. It's showing up in this whole issue around token costs going up as we've started referring to as token maxing. I'm curious if you're seeing any of those kind of issues showing up in your relationships, either with the hyperscalers or with your customers as those underlying costs start to go up and how you're planning longer term against the constraints that seem like they're going to be around for a while in this space. Thanks. thanks Heath Terry, Citi. heath terry citi Really appreciate you taking the time on all of this, particularly the level of detail around some of your technology partnerships. really appreciate you taking the time on all of this particularly the level of detail around some of your technology partnerships The reliance that you have on the cloud providers, they've obviously been very vocal about the issues that they're dealing with from a supply perspective and the constraints with demand increasing the way that it is. the reliance that you have on the cloud providers they've obviously been very vocal about the issues that they're dealing with from a supply perspective and the constraints with demand increasing the way that it is That's showing up in pricing. that's showing up in pricing It's showing up in this whole issue around token costs going up as we've started referring to as token maxing. it's showing up in this whole issue around token costs going up as we've started referring to as token maxing I'm curious if you're seeing any of those kind of issues showing up in your relationships, either with the hyperscalers or with your customers as those underlying costs start to go up and how you're planning longer term against the constraints that seem like they're going to be around for a while in this space. i'm curious if you're seeing any of those kind of issues showing up in your relationships either with the hyperscalers or with your customers as those underlying costs start to go up and how you're planning longer term against the constraints that seem like they're going to be around for a while in this space

Speaker 8: Trygve, you explained to the audience the digital advantage and the partnership model. Why don't we pass this question to you? Trygve, you explained to the audience the digital advantage and the partnership model. trygve you explained to the audience the digital advantage and the partnership model Why don't we pass this question to you? why don't we pass this question to you

Speaker 22: Yeah. As you say, we have a close relationship with all the hyperscalers, all the major cloud providers. We, of course, secure ourselves for our own direct expenses. We secure ourselves with long-term contracts with these providers to ensure that we have cost-competitive access to the technologies. We also work very actively with them, particularly on securing capacity, where we have a well-established playbook for securing that we have the right capacity. As our workloads will be sometimes demanding the same type of capacity they use for other workloads, so make sure that we can continue providing continuity to our customers in operating. Yeah. yeah As you say, we have a close relationship with all the hyperscalers, all the major cloud providers. as you say we have a close relationship with all the hyperscalers all the major cloud providers We, of course, secure ourselves for our own direct expenses. we of course secure ourselves for our own direct expenses We secure ourselves with long-term contracts with these providers to ensure that we have cost-competitive access to the technologies. we secure ourselves with long-term contracts with these providers to ensure that we have cost-competitive access to the technologies We also work very actively with them, particularly on securing capacity, where we have a well-established playbook for securing that we have the right capacity. we also work very actively with them particularly on securing capacity where we have a well-established playbook for securing that we have the right capacity As our workloads will be sometimes demanding the same type of capacity they use for other workloads, so make sure that we can continue providing continuity to our customers in operating. as our workloads will be sometimes demanding the same type of capacity they use for other workloads so make sure that we can continue providing continuity to our customers in operating

Speaker 8: Rakesh, would you like to elaborate further? Rakesh, would you like to elaborate further? rakesh would you like to elaborate further

Speaker 15: Heath, actually, you do make a good point. There is clearly a transition happening, and the industry is getting used to the changes that are happening. I'll say there is a very interesting trend that is happening right now. Instead of going from cloud first, many of our customers are going to what they call hybrid cloud for elasticity. They want to keep on-prem for consistency, and then they go on the edge for immediacy. They are moving in a direction where they will actually have infrastructure which encompasses all of them, so that they're able to take the benefit of what the cloud compute brings as well. They are also prepared so that they are able to get the maximum benefit from what they have in-house already, and also from the edge operations where it is required. Heath, actually, you do make a good point. heath actually you do make a good point There is clearly a transition happening, and the industry is getting used to the changes that are happening. there is clearly a transition happening and the industry is getting used to the changes that are happening I'll say there is a very interesting trend that is happening right now. i'll say there is a very interesting trend that is happening right now Instead of going from cloud first, many of our customers are going to what they call hybrid cloud for elasticity. instead of going from cloud first many of our customers are going to what they call hybrid cloud for elasticity They want to keep on-prem for consistency, and then they go on the edge for immediacy. they want to keep on-prem for consistency and then they go on the edge for immediacy They are moving in a direction where they will actually have infrastructure which encompasses all of them, so that they're able to take the benefit of what the cloud compute brings as well. they are moving in a direction where they will actually have infrastructure which encompasses all of them so that they're able to take the benefit of what the cloud compute brings as well They are also prepared so that they are able to get the maximum benefit from what they have in-house already, and also from the edge operations where it is required. they are also prepared so that they are able to get the maximum benefit from what they have in-house already and also from the edge operations where it is required

Speaker 8: Thank you, Rakesh. Olivier? Thank you, Rakesh. thank you rakesh Olivier? olivier

Speaker 13: What is important to this is that to offer our customers the ability to navigate through this tenant hybrid cloud for elasticity of cloud compute and edge at the same time, doesn't come in a quarter. It has taken us years of deployment, of tuning, of testing and validation, and certification for customer. Proud ourselves to be the only one that can do this complex environment at scale, industry grade, complex architecture that combine the benefits that you heard about, that allow our customers to use the cloud when and as necessary, and remain in that tenant where they believe it is more secure and they have the capacity they can to develop their workflows. That's unique. What is important to this is that to offer our customers the ability to navigate through this tenant hybrid cloud for elasticity of cloud compute and edge at the same time, doesn't come in a quarter. what is important to this is that to offer our customers the ability to navigate through this tenant hybrid cloud for elasticity of cloud compute and edge at the same time doesn't come in a quarter It has taken us years of deployment, of tuning, of testing and validation, and certification for customer. it has taken us years of deployment of tuning of testing and validation and certification for customer Proud ourselves to be the only one that can do this complex environment at scale, industry grade, complex architecture that combine the benefits that you heard about, that allow our customers to use the cloud when and as necessary, and remain in that tenant where they believe it is more secure and they have the capacity they can to develop their workflows. proud ourselves to be the only one that can do this complex environment at scale industry grade complex architecture that combine the benefits that you heard about that allow our customers to use the cloud when and as necessary and remain in that tenant where they believe it is more secure and they have the capacity they can to develop their workflows That's unique. that's unique

Speaker 8: Thank you. In the very back, I see a hand up. Thank you. thank you In the very back, I see a hand up. in the very back i see a hand up

Speaker 20: Hi. Thanks. Stephen Gengaro, Stifel. When we think about digital and we think about maybe the last few years and then now through 2030, how do you think that impacts your growth versus history in the core business? Hi. hi Thanks. thanks Stephen Gengaro, Stifel. stephen gengaro stifel When we think about digital and we think about maybe the last few years and then now through 2030, how do you think that impacts your growth versus history in the core business? when we think about digital and we think about maybe the last few years and then now through 2030 how do you think that impacts your growth versus history in the core business

Speaker 8: Stéphane, let me go ahead and pass this one to you. Did you hear the question? Stéphane, let me go ahead and pass this one to you. stéphane let me go ahead and pass this one to you Did you hear the question? did you hear the question

Speaker 21: Yeah. Actually, if you don't mind rephrasing. Yeah. yeah Actually, if you don't mind rephrasing. actually if you don't mind rephrasing

Speaker 8: Yeah, very good. Stéphane? Yeah, very good. yeah very good Stéphane? stéphane

Speaker 20: maybe relative, unless you want to tell us what you think the market does for the next 5 years, but relative to the market through 2030, how do you think digital impacts the growth in your core operations versus the peer group? maybe relative, unless you want to tell us what you think the market does for the next 5 years, but relative to the market through 2030, how do you think digital impacts the growth in your core operations versus the peer group? maybe relative unless you want to tell us what you think the market does for the next 5 years but relative to the market through 2030 how do you think digital impacts the growth in your core operations versus the peer group

Speaker 21: Okay, got it. Sorry for that. Look, first, the growth we are portraying here for digital, and we've said this before, we believe is at least partially de-correlated from the growth of our core services and equipment, which as you know, are more cyclical. If we are confident to give that 10%-15% CAGR there for digital only, is that we think this is really secular, structural, and triggered more recently by the acceleration of AI. That gives us confidence that there is this pot of digital, if you want, that can grow a bit regardless of what can happen in the rest of the E&P upstream sector. Particularly because it remains a very small % of the total spend, as you've seen. Now, can that influence the size of the overall E&P spend? Yes, it can. Okay, got it. okay got it Sorry for that. sorry for that Look, first, the growth we are portraying here for digital, and we've said this before, we believe is at least partially de-correlated from the growth of our core services and equipment, which as you know, are more cyclical. look first the growth we are portraying here for digital and we've said this before we believe is at least partially de-correlated from the growth of our core services and equipment which as you know are more cyclical If we are confident to give that 10%-15% CAGR there for digital only, is that we think this is really secular, structural, and triggered more recently by the acceleration of AI. if we are confident to give that 10%-15% cagr there for digital only is that we think this is really secular structural and triggered more recently by the acceleration of ai That gives us confidence that there is this pot of digital, if you want, that can grow a bit regardless of what can happen in the rest of the E&P upstream sector. that gives us confidence that there is this pot of digital if you want that can grow a bit regardless of what can happen in the rest of the e&p upstream sector Particularly because it remains a very small % of the total spend, as you've seen. particularly because it remains a very small % of the total spend as you've seen Now, can that influence the size of the overall E&P spend? now can that influence the size of the overall e&p spend Yes, it can. yes it can What it can do, at least for us, is that it can bring more, first more digital. Because, as Cecilia highlighted, it's not just about the software and the platforms, but it is the connection with the hardware, is that more digital is going to pull through more core services as well. We want them to gain in efficiencies and generate cost savings. This is not going to happen in the core services and equipment we provide. To the contrary, we are going to have a boost from the advent of more digital operations. What it can do, at least for us, is that it can bring more, first more digital. what it can do at least for us is that it can bring more first more digital Because, as Cecilia highlighted, it's not just about the software and the platforms, but it is the connection with the hardware, is that more digital is going to pull through more core services as well. because as cecilia highlighted it's not just about the software and the platforms but it is the connection with the hardware is that more digital is going to pull through more core services as well We want them to gain in efficiencies and generate cost savings. we want them to gain in efficiencies and generate cost savings This is not going to happen in the core services and equipment we provide. this is not going to happen in the core services and equipment we provide To the contrary, we are going to have a boost from the advent of more digital operations. to the contrary we are going to have a boost from the advent of more digital operations

Speaker 8: Thank you, Stéphane. Yes, Doug. We'll get you a microphone right here. Thank you, Stéphane. thank you stéphane Yes, Doug. yes doug We'll get you a microphone right here. we'll get you a microphone right here

Speaker 6: Thank you. Doug Becker with Capital One. Curious about, as autonomous operations really start to scale, how are you thinking about risk management? What safeguards are in place from a suboptimal decision made by an autonomous operation or maybe in an extreme example, a well control incident that was really triggered by an autonomous decision? Thank you. thank you Doug Becker with Capital One. doug becker with capital one Curious about, as autonomous operations really start to scale, how are you thinking about risk management? curious about as autonomous operations really start to scale how are you thinking about risk management What safeguards are in place from a suboptimal decision made by an autonomous operation or maybe in an extreme example, a well control incident that was really triggered by an autonomous decision? what safeguards are in place from a suboptimal decision made by an autonomous operation or maybe in an extreme example a well control incident that was really triggered by an autonomous decision

Speaker 8: Thank you, Doug. We're going to pass that one to Cecilia. Thank you, Doug. thank you doug We're going to pass that one to Cecilia. we're going to pass that one to cecilia

Speaker 3: Just like a self-driving car like Tesla, the system can go into manual mode at any time, and the user can decide whether to go autonomous or if the recommendation needs to be approved by the user. It's a very easy on/off, and ultimately, there's always going to be a user that makes the final call, which is going to be our customer. Just like a self-driving car like Tesla, the system can go into manual mode at any time, and the user can decide whether to go autonomous or if the recommendation needs to be approved by the user. just like a self-driving car like tesla the system can go into manual mode at any time and the user can decide whether to go autonomous or if the recommendation needs to be approved by the user It's a very easy on/off, and ultimately, there's always going to be a user that makes the final call, which is going to be our customer. it's a very easy on/off and ultimately there's always going to be a user that makes the final call which is going to be our customer

Speaker 8: Thank you, Cecilia. Saurabh, did you have your hand up? Yeah, right up here in the front, please. Thank you, Cecilia. thank you cecilia Saurabh, did you have your hand up? saurabh did you have your hand up Yeah, right up here in the front, please. yeah right up here in the front please

Speaker 16: Hi, Saurabh Pant, Bank of America. One thing, Olivier, when you took over as the CEO back in 2019, you were talking about the fit-for-basin at that point of time. I think I heard the word fit-for-basin once in Shashi's remarks. How do you think about fit-for-basin from a digital perspective? I know you talked about seven, I think, innovation factories across the globe. Maybe talk to how are you thinking about that? What are you doing differently in different parts of the world? Hi, Saurabh Pant, Bank of America. hi saurabh pant bank of america One thing, Olivier, when you took over as the CEO back in 2019, you were talking about the fit-for-basin at that point of time. one thing olivier when you took over as the ceo back in 2019 you were talking about the fit-for-basin at that point of time I think I heard the word fit-for-basin once in Shashi's remarks. i think i heard the word fit-for-basin once in shashi's remarks How do you think about fit-for-basin from a digital perspective? how do you think about fit-for-basin from a digital perspective I know you talked about seven, I think, innovation factories across the globe. i know you talked about seven i think innovation factories across the globe Maybe talk to how are you thinking about that? maybe talk to how are you thinking about that What are you doing differently in different parts of the world? what are you doing differently in different parts of the world

Speaker 8: Olivier, why don't you go ahead. Olivier, why don't you go ahead. olivier why don't you go ahead

Speaker 13: Yeah. Great question. I think if digital brings us one thing, is ability to customize, to tailor, and to fit our digital frame to the basin challenge that we are facing. I think the concept we have put together with the industrial factory, and we have seven of them in the world, were to provide the digital backbone, the digital domain expert, the digital platform, close to our customer to collaborate on what could be done locally to make fit technology, digital technology solution. Now, with the advent of digital operation, the advent of agentic AI, we are going to the next level. Yeah. yeah Great question. great question I think if digital brings us one thing, is ability to customize, to tailor, and to fit our digital frame to the basin challenge that we are facing. i think if digital brings us one thing is ability to customize to tailor and to fit our digital frame to the basin challenge that we are facing I think the concept we have put together with the industrial factory, and we have seven of them in the world, were to provide the digital backbone, the digital domain expert, the digital platform, close to our customer to collaborate on what could be done locally to make fit technology, digital technology solution. i think the concept we have put together with the industrial factory and we have seven of them in the world were to provide the digital backbone the digital domain expert the digital platform close to our customer to collaborate on what could be done locally to make fit technology digital technology solution Now, with the advent of digital operation, the advent of agentic AI, we are going to the next level. now with the advent of digital operation the advent of agentic ai we are going to the next level The next level of putting together, stitching together OFE operation with digital capability and creating unique set of fit operation with a fit domain foundation model, with fit set of workflows that are stitched together through an agentic AI, and with a fit set of equipment or services provided back to back. The best example actually happening today that we can refer to, it's what you heard about at ADNOC, referring to it as AI PSO. An AI PSO is production optimization using AI. We are co-developing the agents. We are fitting this agent to work on the specific asset of ADNOC, and we are lifting and enhancing the production performance through this. It's a fit application of AI capability tailored to the OEM equipment that they use, tailored to the reservoir characteristics that they have, using our Delfi and our Lumi platform to make it work together. The next level of putting together, stitching together OFE operation with digital capability and creating unique set of fit operation with a fit domain foundation model, with fit set of workflows that are stitched together through an agentic AI, and with a fit set of equipment or services provided back to back. the next level of putting together stitching together ofe operation with digital capability and creating unique set of fit operation with a fit domain foundation model with fit set of workflows that are stitched together through an agentic ai and with a fit set of equipment or services provided back to back The best example actually happening today that we can refer to, it's what you heard about at ADNOC, referring to it as AI PSO. the best example actually happening today that we can refer to it's what you heard about at adnoc referring to it as ai pso An AI PSO is production optimization using AI. an ai pso is production optimization using ai We are co-developing the agents. we are co-developing the agents We are fitting this agent to work on the specific asset of ADNOC, and we are lifting and enhancing the production performance through this. we are fitting this agent to work on the specific asset of adnoc and we are lifting and enhancing the production performance through this It's a fit application of AI capability tailored to the OEM equipment that they use, tailored to the reservoir characteristics that they have, using our Delfi and our Lumi platform to make it work together. it's a fit application of ai capability tailored to the oem equipment that they use tailored to the reservoir characteristics that they have using our delfi and our lumi platform to make it work together That's the principle, that's what we want to extend. That's what we want to repeat from basin to basin. That's the principle, that's what we want to extend. that's the principle that's what we want to extend That's what we want to repeat from basin to basin. that's what we want to repeat from basin to basin

Speaker 8: Trygve, did you wish to add any additional color? Trygve, did you wish to add any additional color? trygve did you wish to add any additional color

Speaker 22: Just there's one more color to fit for basin as well that is increasingly being important now and which is underpinned by our platform investment over the last few years, and that is the technology sovereignty. A lot of operators around the world are increasingly concerned about their sovereignty, their ability to operate their digital environments. This is exactly what our platform has been built for and enabled for the last few years, and I would say we are uniquely positioned to be able to guarantee our customers this type of sovereignty as well. That's the additional thing in addition to the particular operational and geological challenges they have as well. Just there's one more color to fit for basin as well that is increasingly being important now and which is underpinned by our platform investment over the last few years, and that is the technology sovereignty. just there's one more color to fit for basin as well that is increasingly being important now and which is underpinned by our platform investment over the last few years and that is the technology sovereignty A lot of operators around the world are increasingly concerned about their sovereignty, their ability to operate their digital environments. a lot of operators around the world are increasingly concerned about their sovereignty their ability to operate their digital environments This is exactly what our platform has been built for and enabled for the last few years, and I would say we are uniquely positioned to be able to guarantee our customers this type of sovereignty as well. this is exactly what our platform has been built for and enabled for the last few years and i would say we are uniquely positioned to be able to guarantee our customers this type of sovereignty as well That's the additional thing in addition to the particular operational and geological challenges they have as well. that's the additional thing in addition to the particular operational and geological challenges they have as well

Speaker 8: Cecilia. Cecilia. cecilia

Speaker 3: I want to add a different angle to the question. Every geography is going to be different, and the system needs to learn what are the parameters for that geography. For example, a deep water operation is directional drilling is going to look completely different than U.S. land. What the customer wants is going to be completely different. In deep water, it's about landing the operation per the plan in the sweet spot with a minimal amount of risk. In the U.S., it's about drilling as fast as possible. As long as you're in the tunnel, you're fine. The system learns and gets smarter depending on which geography and what type of operations you're running, hence why it's very important to have this wide footprint that we have at SLB. I want to add a different angle to the question. i want to add a different angle to the question Every geography is going to be different, and the system needs to learn what are the parameters for that geography. every geography is going to be different and the system needs to learn what are the parameters for that geography For example, a deep water operation is directional drilling is going to look completely different than U.S. land. for example a deep water operation is directional drilling is going to look completely different than u.s land What the customer wants is going to be completely different. what the customer wants is going to be completely different In deep water, it's about landing the operation per the plan in the sweet spot with a minimal amount of risk. in deep water it's about landing the operation per the plan in the sweet spot with a minimal amount of risk In the U.S., it's about drilling as fast as possible. in the u.s it's about drilling as fast as possible As long as you're in the tunnel, you're fine. as long as you're in the tunnel you're fine The system learns and gets smarter depending on which geography and what type of operations you're running, hence why it's very important to have this wide footprint that we have at SLB. the system learns and gets smarter depending on which geography and what type of operations you're running hence why it's very important to have this wide footprint that we have at slb

Speaker 8: In the very back. Yeah, please keep your hand raised. Thank you. In the very back. in the very back Yeah, please keep your hand raised. yeah please keep your hand raised Thank you. thank you

Speaker 2: Ati Modak from Goldman Sachs. I wanted to connect a few dots. I think Shashi, you mentioned generic LLMs are challenging to do. Olivier, you mentioned at the beginning that it's important to know what to build. We've been hearing customers trying to build their own applications. Where are we in that evolution of that dynamic? I'm curious how that evolution is factored into or affects the sensitivity on your 2030 guidance. Ati Modak from Goldman Sachs. ati modak from goldman sachs I wanted to connect a few dots. i wanted to connect a few dots I think Shashi, you mentioned generic LLMs are challenging to do. i think shashi you mentioned generic llms are challenging to do Olivier, you mentioned at the beginning that it's important to know what to build. olivier you mentioned at the beginning that it's important to know what to build We've been hearing customers trying to build their own applications. we've been hearing customers trying to build their own applications Where are we in that evolution of that dynamic? where are we in that evolution of that dynamic I'm curious how that evolution is factored into or affects the sensitivity on your 2030 guidance. i'm curious how that evolution is factored into or affects the sensitivity on your 2030 guidance

Speaker 8: Shashi, would you like to take the first part of the question? Shashi, would you like to take the first part of the question? shashi would you like to take the first part of the question

Speaker 19: Yeah. I think, we talked about LLMs because they are very powerful tools, but they're very statistical in nature. They build and they generate the next response based on the context you provide. We cannot take that risk when we are talking about technical workflows where customers are making high-value decisions or high-risk decisions, right? What we want to do is to say we will leverage the large language models where they bring value, which is converting the context into an outcome. When the context is set by us, by providing the domain. Yeah. yeah I think, we talked about LLMs because they are very powerful tools, but they're very statistical in nature. i think we talked about llms because they are very powerful tools but they're very statistical in nature They build and they generate the next response based on the context you provide. they build and they generate the next response based on the context you provide We cannot take that risk when we are talking about technical workflows where customers are making high-value decisions or high-risk decisions, right? we cannot take that risk when we are talking about technical workflows where customers are making high-value decisions or high-risk decisions right What we want to do is to say we will leverage the large language models where they bring value, which is converting the context into an outcome. what we want to do is to say we will leverage the large language models where they bring value which is converting the context into an outcome When the context is set by us, by providing the domain. when the context is set by us by providing the domain That means when we are working with a well log foundation model or a seismic foundation model, that absorbs the knowledge that comes from that domain and does the handoff between the foundation model and the large language model to aggregate the information and serve it out, right? That way, we don't ask the large language model to figure out how to work with seismic data. It has no clue, but we do. We work with that balance of us providing the domain context and informing everything based on the domain, and use the large language model for where it is best suited, which is to aggregate and summarize and provide the outcome to the user. That means when we are working with a well log foundation model or a seismic foundation model, that absorbs the knowledge that comes from that domain and does the handoff between the foundation model and the large language model to aggregate the information and serve it out, right? that means when we are working with a well log foundation model or a seismic foundation model that absorbs the knowledge that comes from that domain and does the handoff between the foundation model and the large language model to aggregate the information and serve it out right That way, we don't ask the large language model to figure out how to work with seismic data. that way we don't ask the large language model to figure out how to work with seismic data It has no clue, but we do. it has no clue but we do We work with that balance of us providing the domain context and informing everything based on the domain, and use the large language model for where it is best suited, which is to aggregate and summarize and provide the outcome to the user. we work with that balance of us providing the domain context and informing everything based on the domain and use the large language model for where it is best suited which is to aggregate and summarize and provide the outcome to the user

Speaker 8: I'll pass it to Rakesh. I'll pass it to Rakesh. i'll pass it to rakesh

Speaker 15: Yeah. I think, I want to also bring in Dave's point that I think you were alluding to. Many of our customers have actually tried, absolutely they will continue to try to go down that alley as well. They're realizing more and more that the changes are happening at such a rapid pace that unless you really have the expertise and you're engaged in it on a regular basis, this is not a pace that you will be able to keep up with. Yeah. yeah I think, I want to also bring in Dave's point that I think you were alluding to. i think i want to also bring in dave's point that i think you were alluding to Many of our customers have actually tried, absolutely they will continue to try to go down that alley as well. many of our customers have actually tried absolutely they will continue to try to go down that alley as well They're realizing more and more that the changes are happening at such a rapid pace that unless you really have the expertise and you're engaged in it on a regular basis, this is not a pace that you will be able to keep up with. they're realizing more and more that the changes are happening at such a rapid pace that unless you really have the expertise and you're engaged in it on a regular basis this is not a pace that you will be able to keep up with More and more, we are seeing that the customers are actually aligning with partners that they realize are going to be in this for the long game. The other comment I want to make, we're talking about LLMs a little bit. LLMs are based only on text. The data that we have in our industry is in very other different formats. seismic formats have nothing to do with text. Logs are completely different, and therefore the models, the domain foundation models, naturally, the LLMs cannot do anything with the data that we have in our industry. The domain foundation models have a very distinct application that will continue to bring value to our industry specifically, and only companies who can handle that kind of data will be able to benefit from it as well. I just wanted to give you those two colors. More and more, we are seeing that the customers are actually aligning with partners that they realize are going to be in this for the long game. more and more we are seeing that the customers are actually aligning with partners that they realize are going to be in this for the long game The other comment I want to make, we're talking about LLMs a little bit. the other comment i want to make we're talking about llms a little bit LLMs are based only on text. llms are based only on text The data that we have in our industry is in very other different formats. seismic formats have nothing to do with text. the data that we have in our industry is in very other different formats seismic formats have nothing to do with text Logs are completely different, and therefore the models, the domain foundation models, naturally, the LLMs cannot do anything with the data that we have in our industry. logs are completely different and therefore the models the domain foundation models naturally the llms cannot do anything with the data that we have in our industry The domain foundation models have a very distinct application that will continue to bring value to our industry specifically, and only companies who can handle that kind of data will be able to benefit from it as well. the domain foundation models have a very distinct application that will continue to bring value to our industry specifically and only companies who can handle that kind of data will be able to benefit from it as well I just wanted to give you those two colors. i just wanted to give you those two colors

Speaker 8: Thank you for that, Rakesh. Right here. Dan? Thank you for that, Rakesh. thank you for that rakesh Right here. right here Dan? dan

Speaker 23: Hey, thanks. Good morning. I just wanted to ask a question on labor and kind of talent retention. The catalyst for the question was, I noticed in one of the earlier partner testimonials, it was someone who had actually been at SLB for a couple of decades, and then most recently was at one of your biggest competitors. Yeah. Can you just talk about to what extent attracting talent, retaining talent is a bottleneck or any type of impediment to growth for SLB? Also, if it's something when you speak with your customers, if training and attracting the right talent is a bottleneck for their digital adoption as well? Thanks. Hey, thanks. hey thanks Good morning. good morning I just wanted to ask a question on labor and kind of talent retention. i just wanted to ask a question on labor and kind of talent retention The catalyst for the question was, I noticed in one of the earlier partner testimonials, it was someone who had actually been at SLB for a couple of decades, and then most recently was at one of your biggest competitors. the catalyst for the question was i noticed in one of the earlier partner testimonials it was someone who had actually been at slb for a couple of decades and then most recently was at one of your biggest competitors Yeah. yeah Can you just talk about to what extent attracting talent, retaining talent is a bottleneck or any type of impediment to growth for SLB? can you just talk about to what extent attracting talent retaining talent is a bottleneck or any type of impediment to growth for slb Also, if it's something when you speak with your customers, if training and attracting the right talent is a bottleneck for their digital adoption as well? also if it's something when you speak with your customers if training and attracting the right talent is a bottleneck for their digital adoption as well Thanks. thanks

Speaker 8: Olivier, why don't you? Olivier, why don't you? olivier why don't you

Speaker 13: I think we all compete for the same talent pool. I think we have demonstrated for the last decade that I think we have still the foundation, the culture, the training framework to attract talent, digital talent, geoscience talent, people, technical experts, engineer talent that we train. We co-train in AI and in data science as well as in geoscience domain. We have been able to attract from every region, top talents across the best university. Occasionally, we compete with those hyperscalers. We compete with some other horizontal player. I think the talent we have in our team has allowed us to build what you have seen today, to build the Tela infrastructure, to build the Delfi, to build the Lumi. I think it speaks volume to the talent we have that Shashi is leading and our team is leading. I think we all compete for the same talent pool. i think we all compete for the same talent pool I think we have demonstrated for the last decade that I think we have still the foundation, the culture, the training framework to attract talent, digital talent, geoscience talent, people, technical experts, engineer talent that we train. i think we have demonstrated for the last decade that i think we have still the foundation the culture the training framework to attract talent digital talent geoscience talent people technical experts engineer talent that we train We co-train in AI and in data science as well as in geoscience domain. we co-train in ai and in data science as well as in geoscience domain We have been able to attract from every region, top talents across the best university. we have been able to attract from every region top talents across the best university Occasionally, we compete with those hyperscalers. occasionally we compete with those hyperscalers We compete with some other horizontal player. we compete with some other horizontal player I think the talent we have in our team has allowed us to build what you have seen today, to build the Tela infrastructure, to build the Delfi, to build the Lumi. i think the talent we have in our team has allowed us to build what you have seen today to build the tela infrastructure to build the delfi to build the lumi I think it speaks volume to the talent we have that Shashi is leading and our team is leading. i think it speaks volume to the talent we have that shashi is leading and our team is leading I'm very proud of what we have as a talent pool in our team. I'm convinced we'll continue to attract, I think, these events and what we are publishing every day and the path to autonomy is what is exciting the most new and future employees and prospects that are joining us. They love what they can see when they enter the company. They see that we are becoming a digital-first company, and I think that is very attractive, and I think that is the magnet we are putting for digital talent throughout the next few years. I'm not concerned. I'm excited about the future can give us with this talent pool we are attracting. I'm very proud of what we have as a talent pool in our team. i'm very proud of what we have as a talent pool in our team I'm convinced we'll continue to attract, I think, these events and what we are publishing every day and the path to autonomy is what is exciting the most new and future employees and prospects that are joining us. i'm convinced we'll continue to attract i think these events and what we are publishing every day and the path to autonomy is what is exciting the most new and future employees and prospects that are joining us They love what they can see when they enter the company. they love what they can see when they enter the company They see that we are becoming a digital-first company, and I think that is very attractive, and I think that is the magnet we are putting for digital talent throughout the next few years. they see that we are becoming a digital-first company and i think that is very attractive and i think that is the magnet we are putting for digital talent throughout the next few years I'm not concerned. i'm not concerned I'm excited about the future can give us with this talent pool we are attracting. i'm excited about the future can give us with this talent pool we are attracting

Speaker 8: Thank you, Olivier. Thank you, Olivier. thank you olivier

Speaker 9: Hey, Keith Beckmann from Pickering Energy Partners. It sounded like M&A is probably not a key way to grow. You guys got a lot of internal things going on. On that front, is there anything within the digital portfolio that you think you're missing? Maybe what are some of the key characteristics you're looking for when evaluating potential opportunities? Hey, Keith Beckmann from Pickering Energy Partners. hey keith beckmann from pickering energy partners It sounded like M&A is probably not a key way to grow. it sounded like m&a is probably not a key way to grow You guys got a lot of internal things going on. you guys got a lot of internal things going on On that front, is there anything within the digital portfolio that you think you're missing? on that front is there anything within the digital portfolio that you think you're missing Maybe what are some of the key characteristics you're looking for when evaluating potential opportunities? maybe what are some of the key characteristics you're looking for when evaluating potential opportunities

Speaker 8: Thank you, Keith, for your question. I'll pass that to Rakesh. Thank you, Keith, for your question. thank you keith for your question I'll pass that to Rakesh. i'll pass that to rakesh

Speaker 15: Keith, clearly, we are always on the lookout for bolt-on technologies that will bring value. We've announced a couple, I think, over the last few months that I'm sure you are aware of. I'm not going to sit here and tell you this is the weakness we have in our system. We are always on the lookout for technologies which will complement what we have or for bolt-ons that we decide we will not develop in that particular domain or that particular part of the technology. I think both extending our partnerships with companies that have complementary skills that we will either integrate or we've decided not to compete. Occasionally, where we see that is a good fit into our own organization as we have done, we will continue to look out for opportunities. Keith, clearly, we are always on the lookout for bolt-on technologies that will bring value. keith clearly we are always on the lookout for bolt-on technologies that will bring value We've announced a couple, I think, over the last few months that I'm sure you are aware of. we've announced a couple i think over the last few months that i'm sure you are aware of I'm not going to sit here and tell you this is the weakness we have in our system. i'm not going to sit here and tell you this is the weakness we have in our system We are always on the lookout for technologies which will complement what we have or for bolt-ons that we decide we will not develop in that particular domain or that particular part of the technology. we are always on the lookout for technologies which will complement what we have or for bolt-ons that we decide we will not develop in that particular domain or that particular part of the technology I think both extending our partnerships with companies that have complementary skills that we will either integrate or we've decided not to compete. i think both extending our partnerships with companies that have complementary skills that we will either integrate or we've decided not to compete Occasionally, where we see that is a good fit into our own organization as we have done, we will continue to look out for opportunities. occasionally where we see that is a good fit into our own organization as we have done we will continue to look out for opportunities

Speaker 8: Thank you, Rakesh. I think Destiny Global and Tigo's are good examples of that. Derek. Right here first. Thank you, Rakesh. thank you rakesh I think Destiny Global and Tigo's are good examples of that. i think destiny global and tigo's are good examples of that Derek. derek Right here first. right here first

Speaker 5: Thank you. Derek Podhaizer, Piper Sandler. I found it interesting when you split apart the customer type for digital. I think you had 37% NOC, 37% independents, 21% for the majors. Maybe could you talk about the opportunities to capture more share with the majors or on the flip side, some of the limitations and headwinds to continue to drive adoption in with the majors? Thank you. thank you Derek Podhaizer, Piper Sandler. derek podhaizer piper sandler I found it interesting when you split apart the customer type for digital. i found it interesting when you split apart the customer type for digital I think you had 37% NOC, 37% independents, 21% for the majors. i think you had 37% noc 37% independents 21% for the majors Maybe could you talk about the opportunities to capture more share with the majors or on the flip side, some of the limitations and headwinds to continue to drive adoption in with the majors? maybe could you talk about the opportunities to capture more share with the majors or on the flip side some of the limitations and headwinds to continue to drive adoption in with the majors

Speaker 13: Go ahead. Go ahead. go ahead I think you have seen three statements from Eni, from Chevron, from TotalEnergies, and from Shell. I forgot about Shell in this statement. They're very, very clear of the benefit they've seen partnering with us. They all collaborate with us on a different scope, utilizing digital operation, trying to get the most of autonomy for drilling operations. Chevron is the historical partner that has helped us develop and accelerate our platform at scale with Microsoft. Both Shell and TotalEnergies have entered a collaboration agreement with us to develop fit subsurface and adapt their workflows to the benefits of the organization. I don't see any limitation on this. I see organization on the customer side that are keen and eager to leverage and to work side by side with us so that they can leverage agentic AI environment. I think you have seen three statements from Eni, from Chevron, from TotalEnergies, and from Shell. i think you have seen three statements from eni from chevron from totalenergies and from shell I forgot about Shell in this statement. i forgot about shell in this statement They're very, very clear of the benefit they've seen partnering with us. they're very very clear of the benefit they've seen partnering with us They all collaborate with us on a different scope, utilizing digital operation, trying to get the most of autonomy for drilling operations. they all collaborate with us on a different scope utilizing digital operation trying to get the most of autonomy for drilling operations Chevron is the historical partner that has helped us develop and accelerate our platform at scale with Microsoft. chevron is the historical partner that has helped us develop and accelerate our platform at scale with microsoft Both Shell and TotalEnergies have entered a collaboration agreement with us to develop fit subsurface and adapt their workflows to the benefits of the organization. both shell and totalenergies have entered a collaboration agreement with us to develop fit subsurface and adapt their workflows to the benefits of the organization I don't see any limitation on this. i don't see any limitation on this I see organization on the customer side that are keen and eager to leverage and to work side by side with us so that they can leverage agentic AI environment. i see organization on the customer side that are keen and eager to leverage and to work side by side with us so that they can leverage agentic ai environment They can leverage the powerful platform so that they can deploy to the complex environment they will always want to deploy to match security requirements they have, sovereignty when operate in certain country, and leverage of their own IP, which our platform allows us to plug in. I don't see a cycle. I see a big runway with all the major and the ones that were mentioned into this to continue to work with them for adoption at scale. They can leverage the powerful platform so that they can deploy to the complex environment they will always want to deploy to match security requirements they have, sovereignty when operate in certain country, and leverage of their own IP, which our platform allows us to plug in. they can leverage the powerful platform so that they can deploy to the complex environment they will always want to deploy to match security requirements they have sovereignty when operate in certain country and leverage of their own ip which our platform allows us to plug in I don't see a cycle. i don't see a cycle I see a big runway with all the major and the ones that were mentioned into this to continue to work with them for adoption at scale. i see a big runway with all the major and the ones that were mentioned into this to continue to work with them for adoption at scale

Speaker 8: Very good. Right here. Very good. very good Right here. right here

Speaker 14: Thanks. Phillip Jungwirth with BMO. Can you talk about the drivers behind the margin improvement by 2030, 38%-42% is quite a bit higher than 35% in 2025, and I think you guided a similar level here in 2026, despite the 9% growth. Is it mainly just mix shift with platforms and applications, digital operations growing more, or is there more behind it? If so, could you please expand upon that? Thanks. Thanks. thanks Phillip Jungwirth with BMO. phillip jungwirth with bmo Can you talk about the drivers behind the margin improvement by 2030, 38%-42% is quite a bit higher than 35% in 2025, and I think you guided a similar level here in 2026, despite the 9% growth. can you talk about the drivers behind the margin improvement by 2030 38%-42% is quite a bit higher than 35% in 2025 and i think you guided a similar level here in 2026 despite the 9% growth Is it mainly just mix shift with platforms and applications, digital operations growing more, or is there more behind it? is it mainly just mix shift with platforms and applications digital operations growing more or is there more behind it If so, could you please expand upon that? if so could you please expand upon that Thanks. thanks

Speaker 8: Very good. Stéphane, I'm going to pass this one right to you. Very good. very good Stéphane, I'm going to pass this one right to you. stéphane i'm going to pass this one right to you

Speaker 21: Look, first, I'm quite confident we can reach that range towards the end of the decade, if not earlier. I think actually margins will increase year after year into 2030 to reach these levels. The key driver is a few things. First, you have the simple operating leverage. We've mentioned R&D before. R&D, if you want, is the biggest cost to grow. Again, the heavy lifting is done, and if we increase R&D a little bit, it's not going to increase for sure as much as the revenue growth. You get margin expansion from there, you have that shift in pricing model. Some of it is enabled by AI. We believe we will be able to increase the subscription-based revenue, which allows us to tier better, if you want, the levels of pricing, depending on the features each customer use. Look, first, I'm quite confident we can reach that range towards the end of the decade, if not earlier. look first i'm quite confident we can reach that range towards the end of the decade if not earlier I think actually margins will increase year after year into 2030 to reach these levels. i think actually margins will increase year after year into 2030 to reach these levels The key driver is a few things. the key driver is a few things First, you have the simple operating leverage. first you have the simple operating leverage We've mentioned R&D before. we've mentioned r&d before R&D, if you want, is the biggest cost to grow. r&d if you want is the biggest cost to grow Again, the heavy lifting is done, and if we increase R&D a little bit, it's not going to increase for sure as much as the revenue growth. again the heavy lifting is done and if we increase r&d a little bit it's not going to increase for sure as much as the revenue growth You get margin expansion from there, you have that shift in pricing model. you get margin expansion from there you have that shift in pricing model Some of it is enabled by AI. some of it is enabled by ai We believe we will be able to increase the subscription-based revenue, which allows us to tier better, if you want, the levels of pricing, depending on the features each customer use. we believe we will be able to increase the subscription-based revenue which allows us to tier better if you want the levels of pricing depending on the features each customer use More consumption-based, more outcome-based pricing should help us lift the margins as well. It's the combination of all this that really gives us the confidence that 38%-42%, the midpoint of 40%, if you want, is quite a good ambition I think we can reach. More consumption-based, more outcome-based pricing should help us lift the margins as well. more consumption-based more outcome-based pricing should help us lift the margins as well It's the combination of all this that really gives us the confidence that 38%-42%, the midpoint of 40%, if you want, is quite a good ambition I think we can reach. it's the combination of all this that really gives us the confidence that 38%-42% the midpoint of 40% if you want is quite a good ambition i think we can reach

Speaker 8: Thank you for that perspective. Allow me to come back to this side of the audience. Yes, right here. Thank you for that perspective. thank you for that perspective Allow me to come back to this side of the audience. allow me to come back to this side of the audience Yes, right here. yes right here

Speaker 12: Hi. Noah Naparstek from Goldman Sachs. I have another question on the mix. If we look at the 60% or so of revenues that's recurring and repeating, just wondering how weighted it is to pure SaaS. Do you plan to increase SaaS mix over time? How do you plan to do that? Hi. hi Noah Naparstek from Goldman Sachs. noah naparstek from goldman sachs I have another question on the mix. i have another question on the mix If we look at the 60% or so of revenues that's recurring and repeating, just wondering how weighted it is to pure SaaS. if we look at the 60% or so of revenues that's recurring and repeating just wondering how weighted it is to pure saas Do you plan to increase SaaS mix over time? do you plan to increase saas mix over time How do you plan to do that? how do you plan to do that

Speaker 8: Yes. I'll pass it back to Stéphane. Yes. yes I'll pass it back to Stéphane. i'll pass it back to stéphane

Speaker 21: Yeah. Definitely we do, yes. It's part of the driver is indeed the SaaS mix. Again, we are not betting everything on the cloud, right? Because as we mentioned before, we leave the customers where they are. Still, we are seeing that shift. Is it going as fast as we want it to be? Maybe not, but it is going. Today, we have, if you want, a bit less than 50% on the cloud, and we could very much go to around 75% at one stage of SaaS and cloud. It's part of it. Yeah. yeah Definitely we do, yes. definitely we do yes It's part of the driver is indeed the SaaS mix. it's part of the driver is indeed the saas mix Again, we are not betting everything on the cloud, right? again we are not betting everything on the cloud right Because as we mentioned before, we leave the customers where they are. because as we mentioned before we leave the customers where they are Still, we are seeing that shift. still we are seeing that shift Is it going as fast as we want it to be? is it going as fast as we want it to be Maybe not, but it is going. maybe not but it is going Today, we have, if you want, a bit less than 50% on the cloud, and we could very much go to around 75% at one stage of SaaS and cloud. today we have if you want a bit less than 50% on the cloud and we could very much go to around 75% at one stage of saas and cloud It's part of it. it's part of it

Speaker 8: Olivier. Olivier. olivier

Speaker 13: The other element is the consumption model as part of the science. I think the use of AI, the use of agent, as you have seen a demo, as was shown by Shashi earlier today, you can imagine the compounding effect of deploying agents that can then run autonomously part of our engines that are either on the cloud or on the tenants, and consumption is based on the frequency and intensity of use of this application. That's this compounding effect that we believe will drive the way forward. The other element is the consumption model as part of the science. the other element is the consumption model as part of the science I think the use of AI, the use of agent, as you have seen a demo, as was shown by Shashi earlier today, you can imagine the compounding effect of deploying agents that can then run autonomously part of our engines that are either on the cloud or on the tenants, and consumption is based on the frequency and intensity of use of this application. i think the use of ai the use of agent as you have seen a demo as was shown by shashi earlier today you can imagine the compounding effect of deploying agents that can then run autonomously part of our engines that are either on the cloud or on the tenants and consumption is based on the frequency and intensity of use of this application That's this compounding effect that we believe will drive the way forward. that's this compounding effect that we believe will drive the way forward

Speaker 8: Do we have any further questions from the audience? Yes. Right here. Do we have any further questions from the audience? do we have any further questions from the audience Yes. yes Right here. right here

Speaker 10: Thank you. Keith Mackey with RBC. The digital operations TAM expansion is certainly key to the growth metrics here. Can you just talk about what some of the key customer impediments to adopting digital operations has been, and how do you mitigate that to drive the further adoption going forward? Thank you. thank you Keith Mackey with RBC. keith mackey with rbc The digital operations TAM expansion is certainly key to the growth metrics here. the digital operations tam expansion is certainly key to the growth metrics here Can you just talk about what some of the key customer impediments to adopting digital operations has been, and how do you mitigate that to drive the further adoption going forward? can you just talk about what some of the key customer impediments to adopting digital operations has been and how do you mitigate that to drive the further adoption going forward

Speaker 8: Thank you, Keith, for the question. Cecilia? Thank you, Keith, for the question. thank you keith for the question Cecilia? cecilia

Speaker 3: Sure. Thanks for the question. Excellent question, in fact. What we see is that customers like to pilot and test the system first to really understand the value it brings and to ensure that it's a safe operations and it fits everything that they would like to see out of the tool. Just to give you an idea, the last 6 months, we've done as much autonomous feats drilled than the first 2 and a half years. It's taken us quite some time to get those pilots, to get our customers to feel comfortable with it. Now we're starting to see quite a lot of uptake and an acceleration of uptake. The second thing is that a lot of customers are waiting to see who's going to go first. Sure. sure Thanks for the question. thanks for the question Excellent question, in fact. excellent question in fact What we see is that customers like to pilot and test the system first to really understand the value it brings and to ensure that it's a safe operations and it fits everything that they would like to see out of the tool. what we see is that customers like to pilot and test the system first to really understand the value it brings and to ensure that it's a safe operations and it fits everything that they would like to see out of the tool Just to give you an idea, the last 6 months, we've done as much autonomous feats drilled than the first 2 and a half years. just to give you an idea the last 6 months we've done as much autonomous feats drilled than the first 2 and a half years It's taken us quite some time to get those pilots, to get our customers to feel comfortable with it. it's taken us quite some time to get those pilots to get our customers to feel comfortable with it Now we're starting to see quite a lot of uptake and an acceleration of uptake. now we're starting to see quite a lot of uptake and an acceleration of uptake The second thing is that a lot of customers are waiting to see who's going to go first. the second thing is that a lot of customers are waiting to see who's going to go first Now we have enough pilots that we're actually seeing customers almost not wanting to be left behind, and they're starting to be very interested in what we have to offer. Now we have enough pilots that we're actually seeing customers almost not wanting to be left behind, and they're starting to be very interested in what we have to offer. now we have enough pilots that we're actually seeing customers almost not wanting to be left behind and they're starting to be very interested in what we have to offer

Speaker 8: We have time for one final question. Yes. Right there. We have time for one final question. we have time for one final question Yes. yes Right there. right there

Speaker 7: Thank you. Heath Terry again from Citi. You obviously have operated for a very long time in some of the most geopolitically sensitive parts of the world. This past weekend, we got a bit of a wake-up call with the U.S. government's decision to effectively ban access to one of the large language models. How does that potentially impact the way that you and your customers are operating around this? Does it lead you to want to use more open source? Does it lead you to want to have more distributed systems in terms of where your own technology or where your customer technology is sitting? Thank you. thank you Heath Terry again from Citi. heath terry again from citi You obviously have operated for a very long time in some of the most geopolitically sensitive parts of the world. you obviously have operated for a very long time in some of the most geopolitically sensitive parts of the world This past weekend, we got a bit of a wake-up call with the U.S. government's decision to effectively ban access to one of the large language models. this past weekend we got a bit of a wake-up call with the u.s government's decision to effectively ban access to one of the large language models How does that potentially impact the way that you and your customers are operating around this? how does that potentially impact the way that you and your customers are operating around this Does it lead you to want to use more open source? does it lead you to want to use more open source Does it lead you to want to have more distributed systems in terms of where your own technology or where your customer technology is sitting? does it lead you to want to have more distributed systems in terms of where your own technology or where your customer technology is sitting

Speaker 8: Thank you for that final question. Shashi, why don't you go ahead and take the question, and then we'll leave it to Olivier for closing remarks. Thank you for that final question. thank you for that final question Shashi, why don't you go ahead and take the question, and then we'll leave it to Olivier for closing remarks. shashi why don't you go ahead and take the question and then we'll leave it to olivier for closing remarks

Speaker 19: Yeah. It's a very good question. I think when we started this journey, the LLM providers was few and select, but now the level of capabilities that we will need from an LLM to integrate into our technical solutions is getting to a point that you can get it from a large number of providers. What we have done is that while we leave this choice of a specific LLM to a customer because they may have an internal enterprise-level choice, we also make sure that we implement our technology stack from the point of view of supporting open models. We partner with NVIDIA, we have NVIDIA's Nemotron models as the models that we can deploy ourselves. We don't have to wait for a CSP to provide it in a particular area. It can be deployed on-prem or within a customer's environment. Yeah. yeah It's a very good question. it's a very good question I think when we started this journey, the LLM providers was few and select, but now the level of capabilities that we will need from an LLM to integrate into our technical solutions is getting to a point that you can get it from a large number of providers. i think when we started this journey the llm providers was few and select but now the level of capabilities that we will need from an llm to integrate into our technical solutions is getting to a point that you can get it from a large number of providers What we have done is that while we leave this choice of a specific LLM to a customer because they may have an internal enterprise-level choice, we also make sure that we implement our technology stack from the point of view of supporting open models. what we have done is that while we leave this choice of a specific llm to a customer because they may have an internal enterprise-level choice we also make sure that we implement our technology stack from the point of view of supporting open models We partner with NVIDIA, we have NVIDIA's Nemotron models as the models that we can deploy ourselves. we partner with nvidia we have nvidia's nemotron models as the models that we can deploy ourselves We don't have to wait for a CSP to provide it in a particular area. we don't have to wait for a csp to provide it in a particular area It can be deployed on-prem or within a customer's environment. it can be deployed on-prem or within a customer's environment Similarly, we have models from Mistral. We have several options. We keep that options open. Even our own domain foundation models start from a base model that is open source, so that we are not tied down to a particular provider and get our hands in a bind at some point in time. Similarly, we have models from Mistral. similarly we have models from mistral We have several options. we have several options We keep that options open. we keep that options open Even our own domain foundation models start from a base model that is open source, so that we are not tied down to a particular provider and get our hands in a bind at some point in time. even our own domain foundation models start from a base model that is open source so that we are not tied down to a particular provider and get our hands in a bind at some point in time

Speaker 13: It matters to our customer. They realize when they are walking with us through and discover the way we have built this model, the way we have factored open source or open protocol into our Tela framework, into our Lumi, into our GenAI, reinforce the attractiveness and the confidence they can bet on this technology platform for the future. Just to conclude, I think we had run through for the last more than two hours. I hope we convince you that I think we have a unique moat as a digital leader in our industry. We are building it on four clearly distinct combined capabilities, deep domain expertise that is rooted 100 years ago, a platform approach that includes an AI-ready stack, an ecosystem with partners that you have heard about that is unique and are willing to, and making every effort to work with us. It matters to our customer. it matters to our customer They realize when they are walking with us through and discover the way we have built this model, the way we have factored open source or open protocol into our Tela framework, into our Lumi, into our GenAI , reinforce the attractiveness and the confidence they can bet on this technology platform for the future. they realize when they are walking with us through and discover the way we have built this model the way we have factored open source or open protocol into our tela framework into our lumi into our genai reinforce the attractiveness and the confidence they can bet on this technology platform for the future Just to conclude, I think we had run through for the last more than two hours. just to conclude i think we had run through for the last more than two hours I hope we convince you that I think we have a unique moat as a digital leader in our industry. i hope we convince you that i think we have a unique moat as a digital leader in our industry We are building it on four clearly distinct combined capabilities, deep domain expertise that is rooted 100 years ago, a platform approach that includes an AI-ready stack, an ecosystem with partners that you have heard about that is unique and are willing to, and making every effort to work with us. we are building it on four clearly distinct combined capabilities deep domain expertise that is rooted 100 years ago a platform approach that includes an ai-ready stack an ecosystem with partners that you have heard about that is unique and are willing to and making every effort to work with us Finally, ability to scale. Not only to scale AI, but to scale in digital operation and to scale and use the footprint and sandbox of our oilfield services and equipment potential. To reach all of our customers and to then help transform this industry to be digital first. That's the way we are willing to lead the future, to be recognized as digital-first company that help transform and unlock new level of efficiency, performance, and value for this industry. We believe we are there to lead this, to create this shift that industry needs for energy security, for energy affordability, and for the future of growth in our societies. That's where we believe we have a role to play, and that's what we wanted to share with you today. Again, thank you for joining us. Finally, ability to scale. finally ability to scale Not only to scale AI, but to scale in digital operation and to scale and use the footprint and sandbox of our oilfield services and equipment potential. not only to scale ai but to scale in digital operation and to scale and use the footprint and sandbox of our oilfield services and equipment potential To reach all of our customers and to then help transform this industry to be digital first. to reach all of our customers and to then help transform this industry to be digital first That's the way we are willing to lead the future, to be recognized as digital-first company that help transform and unlock new level of efficiency, performance, and value for this industry. We believe we are there to lead this, to create this shift that industry needs for energy security, for energy affordability, and for the future of growth in our societies. that's the way we are willing to lead the future to be recognized as digital-first company that help transform and unlock new level of efficiency performance and value for this industry. we believe we are there to lead this to create this shift that industry needs for energy security for energy affordability and for the future of growth in our societies That's where we believe we have a role to play, and that's what we wanted to share with you today. that's where we believe we have a role to play and that's what we wanted to share with you today Again, thank you for joining us. again thank you for joining us I hope that you got enough information to help you model the future and recognize what you believe will be an elevated multiple for the company going forward. Thank you very much. I hope that you got enough information to help you model the future and recognize what you believe will be an elevated multiple for the company going forward. i hope that you got enough information to help you model the future and recognize what you believe will be an elevated multiple for the company going forward Thank you very much. thank you very much

Speaker 8: Thank you, everyone. That completes the formal portion of our program today. On behalf of the entire team, we thank you for your time, your thoughtful questions, and your continued engagement. We hope today's session clearly demonstrated not just the current strength of our digital business, but the distinct competitive advantages that will drive our next phase of growth. We are incredibly excited about the opportunities ahead and our ability to deliver long-term value for our shareholders. With that, we will conclude today's livestream. Thank you, everyone. thank you everyone That completes the formal portion of our program today. that completes the formal portion of our program today On behalf of the entire team, we thank you for your time, your thoughtful questions, and your continued engagement. on behalf of the entire team we thank you for your time your thoughtful questions and your continued engagement We hope today's session clearly demonstrated not just the current strength of our digital business, but the distinct competitive advantages that will drive our next phase of growth. we hope today's session clearly demonstrated not just the current strength of our digital business but the distinct competitive advantages that will drive our next phase of growth We are incredibly excited about the opportunities ahead and our ability to deliver long-term value for our shareholders. we are incredibly excited about the opportunities ahead and our ability to deliver long-term value for our shareholders With that, we will conclude today's livestream. with that we will conclude today's livestream