Veritone, Inc. — Call Transcript 2026

Afternoon, and welcome to the Needham Technology, & Media Conference. This afternoon we're excited to have Veritone, with CEO Ryan Steelberg. Hey, Josh. Great to be here. Yeah. All right. Ryan, maybe we can start with an overview of Veritone for those less familiar and the transformation that you've accomplished in the business over the last couple years. Well, Veritone's been around a little over 10 years. We were kind of one of the first AI-based companies to really go after the unstructured data market. I come from a media entertainment ad tech background, and we felt that there was a gonna be a huge problem of the creation of a lot of unstructured data. If you kind of think about what Google and other search engines of the past did with structured data and text and HTML, we had a vision of what if you can ingest and start to index and understand all this audio and video. I came from Google. That was my job working for Sheryl Sandberg and Tim Armstrong, was: How can we start to understand what's inside audio/video? Primarily, to frankly sell more advertising space. We spun off. The vision of Veritone was imagine a world where any type of audio and video, whether it's streaming audio, it's television, it's security cameras, if we can index all this audio and video, we could really unlock a lot of value and efficiencies across the board. Started the business in 2014. We still work with many of our original customers in the media entertainment space, and we've expanded a lot into public sector, state and local law enforcement. We work for the Department of War. We've been doing that for a while. One problem when you start really early is when we were kind of waiting for, I'd say, the AI market to mature, we did get a little fragmented as a business. We started to go into many different lines of business, going back several years. It really for us, over the last few years, was just getting back to our roots, our original thesis of can we just service, you know, our media entertainment customers, our police agencies, our Air Force customers, with, I would say, singular focus and that's what we've done. In addition to that, which you can kinda read by some of our filings, is, you know, we did have a lot of debt in the past, where, you know, we've paid off a lot of it, and we're down about $45 million of total debt, down from a peak of over $230 million of debt. I think you're looking at Veritone as kind of a Although it's a lot of the same people, I'm still here, it's kind of a renewed focus, a renewed vision, and a much better balance sheet and, I'll say, fiscal responsibility. Got it. Along with that, you spun off the advertising business. Yeah I guess, how long ago was that now? 18 months ago? Well, Yeah, that was in Q4 2024. Part of it was, you know, again, there was just some peripheral businesses that I think were impeding some of our growth, which we've kind of shedded those, and now we're kind of back to our kinda core AI software business. Got it. All right. You just reported Q1 this morning, and obviously now we're here doing a fireside chat. Maybe to catch people up on the quarter, what would you say were some of the key highlights from the Q1 results? I think first of all was, you know, revenue was relatively flat year-over-year. I think the big highlights for us was a huge expansion in our pipeline for some of our new data lines of business called VDR, Veritone Data Refinery. We're gonna talk a little bit about that in the future. We did announce some very key signings of two mega new clients of ours, Google and NVIDIA, where we are now, I'd say, a Tier 1 partner of theirs, helping prepare, package and license training data to them, somewhat akin to like a Scale AI, if you're familiar with that business. That's definitely another highlight. And I think a third is just the velocity and growth of our public safety business. 69% year-over-year on a quarterly basis in terms of growth. You know, new activation with the Air Force and the Defense Logistics Agency, which we'll go into. I think it was a combination of, again, just improvements of operational efficiency, expansion of the pipeline, and thankfully landing, which we're probably about a quarter overdue, some of them are more bellwether contract with Google and NVIDIA. Got it. All right. VDR obviously is, kinda the key upswing factor in your business model right now. Maybe you could just start off by explaining what do you do with this VDR platform, and maybe why is it differentiated versus your competitors? Veritone Data Refinery, for 10 years, we have been ingesting and indexing tens of millions of hours of audio and video for our customers. Those range from CBS News to the Masters Tournament to security camera footage. Organically, about two years ago, we really start to see how a lot of the large hyperscaler companies who are building foundational models, the OpenAIs of the world, the Geminis, they really started to need a tremendous amount of clean, IP-cleared audio and video for training data. Obviously, these models were originally trained on primarily text. They've advanced to imagery, now audio and video and other forms of unstructured data. Veritone organically has been processing and indexing this audio and video dataset for years. We made the decision to introduce that new line of business, named the Veritone Data Refinery, then we've started to package and start to license those datasets to many of the largest hyperscalers out there. We're thrilled about it. We're very excited about it. What makes us really unique is, first, I would say, you know, our expertise in understanding the audio and video datasets. It's probably second to none. That's really where we cut our teeth. You kind of say if you think of AI and audio and video understanding and indexing, I think that's really where Veritone shines for a multitude of reasons, scale, efficiency, and frankly the end, I'd say the output of our processing to prepare the datasets for AI-based processing. The second is our supply. As Mike, our CFO, touched on in our earnings, we've been signing a tremendous amount of supply with partners to the tunes of, you know, 50 million hours of plus of data that we're able to now leverage and introduce those datasets to hyperscalers. We've created, in effect, a kind of a multi-tier moat here, a huge repository of proprietary data assets to prepare and license. That we have now also signed, which we also announced, is really almost every single foundational model player, that are also under contract. We sit on both sides. We have a representation agreement with supply. Now we have signed contracts on the VDR side with all the buyers. We're in a fantastic situation finally to start, let's say, you know, sprinting and executing on the VDR business. Maybe just to touch on, you know, what makes it difficult to index and make unstructured data searchable? Is there something inherent in the way that the data is, like, put together that makes it difficult? How have you kinda like, you know, overcome that, the difficulties with that? I think, well, first is the scale. When, you know, understanding audio and video, obviously the models are getting more mature. Typically, when you see a lot of these use cases, you're dealing with minutes or a few hours of content, candidly. When you're talking about archives that have hundreds of thousands or even millions of hours, that is a tremendous amount of processing, and frankly, expense. When you're thinking about trying to prepare datasets for large language models, they don't need just a couple hundred hours. Often, they need thousands or tens of thousands or hundreds of thousands of hours. This is as much, I'll call, an orchestration dealing with the details of bitrate and quality and performance of the video files themselves, as much as it is leveraging the cognitive science of turning that into structured data with temporal metadata. I think it's, for Veritone, it's the combination of both expertise on the underlying aspects of audio and video, going back a very long time of understanding audio and video in the media and entertainment space, coupled with our expertise in I'll call cognitive AI, that combination has proven to be very effective in servicing, frankly, the highest demanding customers out there, which are the hyperscalers. One other thing to note is when we prepare these datasets for the different, aforementioned customers, they all want it slightly different, right? Don't think of it as just us transferring a video file over. There's a lot of work that we have to do and prepare it differently for company A, like a Meta, versus somebody else, like an AWS. Got it. Okay. Super helpful. All right. If we look at the VDR opportunity, it seems like the near-term kinda major revenue opportunities remain with the largest hyperscalers. Is that the case, and how does that dynamic factor into the implied, second half, ramp in revenue based on your guidance? I mean, you think we read in the press, right? The largest budgets that are funding this huge infrastructure build-out are these large hyperscalers, right? The data investment into data training sense is no different, right? What we did project is we do expect for this year at a minimum, the super majority of our revenues from the VDR are gonna come from these largest hyperscalers. That being said, because the cost of compute, the cost of storage, and I'll say the efficiencies of a lot of the AI models or the ability to train models, that bar is coming down. We are seeing an expansion of the type and number of customers. Yeah, and don't wanna drop, you know, some names, but let's just say that you wouldn't readily think that they're in the business now of training AI models. To be clear, at least for 2026, it's gonna be dominated by the Metas of the world and the AWSs of the world. Got it. All right. Then maybe just to wrap up that point, the implied second half ramp and the revenue, what gives you kinda confidence in terms of what you're seeing behind the scenes to make sense that there is gonna be some upward trajectory to that revenue? We may not know the-precise dynamic, but- I think, well, two keys is one, some of the supply we've been talking about, was recently just signed, right? As, you know, let's say as late Q4. The amount of data that we have access to prepare, to package, to sell has greatly increased by stuff that was recently bought on board under contract in late Q4. Think of it as much more supply. Number two is, as we've just touched on, two of the biggest players in the entire space didn't even come under contract until late February. Right. If you kinda look at those two huge components in terms of fuel, right, or limiting factors, those have been sort of satisfied. The third element is, which we touched on, is our near-term pipeline is almost $70 million now for VDR, with a material amount of that already out for a quote, if you will, for booking. I think it's just, we were talking about such a compressed period of time here of semantics of a few weeks. If you kinda project that forward, we're very bullish on what that pipeline looks like and how we're gonna be able to mobilize that pipeline through 2026. Got it. That's super helpful. All right. You have an open platform approach where customers can bring in any third-party AI models. Can you explain why that's the right product strategy versus a closed-loop system, some of your competitors pursue? Maybe on top of that, are some of the competitors that did have closed-loop systems adjusting their approach? Yeah because they realized it was a mistake? Let me reset for the audience in here. We're not talking about necessarily VDR anymore. Yes Let's go back to how I'm servicing ESPN, right? If I'm ingesting all of ESPN's content from all these different sources, we build bespoke recipes of different AI and cognition to turn it into structured metadata. Question would be, okay, great, you know, there's, you know, at the, you know, three years ago, we were using, let's say, a fine-tuned transcription model that's good for global English, hypothetically. If you, in this space, the one thing that's always constant is change, okay? It's a little cliché, but every single day, we're not seeing more innovation as it relates to models. Not just large language models, not just large multimodality models, but bespoke models like object detection, face detection, et cetera. From day one, our thesis was, and this goes back all the way to 2014, was we made a bet that there was gonna be millions of models, right? I'm not gonna say we were clairvoyant in saying that we were gonna see the, necessarily the large language models, but what you're seeing today, right, is we're still seeing better efficiency and accuracy for hyper-trained, narrow cognitive models for certain things, like finding a Honda Accord 1983 with a blue dent in the back. That can be trained, right? I don't know why you're grinning. Maybe it was the car that you stole. Working in concert, well, I'll say with general understanding of video, that could be more appropriate with a large video-based model. Yeah. What we've seen time and time again is when you can blend these art forms, you get the both worlds. You get the best accuracy, and you can do it at phenomenal price. Remember, a lot of the data that we're talking about, the volume is so big, and a lot of it can't leave our environment. I can't take our video, for example, from ESPN or take our data from a police investigation and necessarily load it into a publicly hosted large model. Okay? First of all, I'm not even allowed to move it often, right? The datasets. Or two, the volume is so big that if you kinda look at the cost of the tokens and the processing for these, it'd be cost prohibitive. I'd be spending tens of millions of dollars a year just to create the metadata. Our job is, without ruining the application or the workflow experience, if there's a better model on the market, our goal is to get it onboarded as a hosted, a containerized model onto the aiWARE stack, which is our proprietary stack, as quickly as possible. One thing to note is roughly about 30% of the models that we've invoked over the last, like for example, 24 months, are Veritone's proprietary trained models, right? Meaning we don't care, right? If there's a better model that has better yield, better productivity, we wanna have that onboarded onto our stack as quickly as possible without disrupting the customer's experience at all. Got it. All right. In terms of the public safety, part of your business, how do you continue to build awareness with customers of your position in the marketplace, while at the same time work within customer budgets to kinda get a foot in the door? We'll break this into two parts. We'll do SLED, state and local law enforcement, and kind of federal government. In state and local law enforcement, there's a few legacy titan players. Axon is a major player. Flock is a major player. Motorola is a major player. What we're seeing is a lot of these groups come in as almost a vertical stack. Vendor lock-in is something that's scary to everybody. This is a real issue. And also the price points that a lot of these legacy companies are coming to bear are very expensive. Police agencies, sheriff departments, municipalities are under major budget constraints. If you take the culmination of, frankly, us coming in later with, I'd say, an open platform framework that we can use with any data source, right, any type of player, it's fascinating. The best way I can describe it is almost 40% of our current customer base is also an Axon customer. They're also a Motorola customer. What I mean by that is Veritone sits on top. Think of it as a data abstraction layer that sits on top of any deployed infrastructure. I don't care where, what body camera, platform they have. I don't care what CCTV or drone provider they have. The key is for us to come in very cost effectively and create that intelligence data layer on top. The goal here is I wanna solve crime faster, right? I wanna be able to ingest the data from any cell phone, from any CCTV camera, and if I can help that investigator move that case along and increase their case closure rate faster, everybody wins. The other byproduct is they don't have to necessarily be over-reliant or basically take, at times, inferior solutions. I would say is our end applications, our redaction software, our investigation software is best of breed. We can compete against anybody, and so therefore, we are encouraging working with with the cities directly and with other competitors, other body camera companies, et cetera, as a, I'll say a partner horizontal complementor. Do we wanna provide the LAPD with the best of breed solution end to end? They shouldn't be forced to take a vertical lock-in that's overpriced and frankly has stuff that's an inferior product. Got it. All right. As you think about the future product roadmap for public sector, how are you thinking about selling just the straight platform to customers versus selling individual applications? Maybe explaining that might be helpful. Right now, our core stack is called aiWARE. Every application we build for commercial, like the ESPNs or the applications or workflows we build for the federal government or state and local law enforcement, are built on top of aiWARE. The majority of our revenue is actually being derived from us licensing and them using those end applications. Think of it as Windows versus Microsoft Office, right? Everybody knows that Windows and other operating systems have SDKs. You can build your own proprietary applications on those. By the way, you can do the same thing with aiWARE. Far, we've had the most success of selling our applications. What we are seeing, and I think that's going to be case for smaller agencies, right, who have limited technical resources or budgets, we don't envision them building necessarily custom applications or solutions today on aiWARE. The larger agencies, yes, because their use cases are more diversified, they're more complicated, and frankly, they have so many different departments that us reimagining what a, an improved workflow or a custom application for like, let's say, LAPD, makes a lot of sense, right? Versus you force-feeding them, right, I say a smaller or limited scope application. Very simply is I do see us still being more successful selling applications, AI-based applications to smaller firms. Larger firms, you'll start to see more custom builds and solutions built on aiWARE, which is what we're seeing in the Fed. U.S. Senate, the Air Force, Defense Logistics Agency, by the way, they all started with buying single applications. Every one of those clients now are building or frankly at times engaging us to build custom workflows and applications. Not just taking the off the shelf applications, but doing something that's larger or more custom for their type of organization. How does that compare to your kind of historical kind of dominance or strength in the media and entertainment vertical where you were just selling the platform? Why did it make sense for you, for those customers primarily to buy the platform and not build individual applications for those customers? Well, actually, we have, we very rarely ever sold just the platform in the past to media and entertainment. Okay. It's almost always been the application layer, right? Of selling into media and entertainment, right? Very rarely were they buying, for example, Maybe if the first couple years, with like Disney and a couple others, we were simply, they were accessing our APIs and building custom solutions on top of that. That was not very successful in 2014 through 2018. It was too early in the space. It's kinda like, people didn't have a webmaster back in the day, right? Even though you could build very easy websites in HTML, people frankly just wanted turnkey applications back then. Just to be clear, what gave us all the benefit was thankfully the way we designed the workflow and the SDK of aiWARE afforded us the ability to build these applications so cost effectively, right? That are very competitive or extensible. What you're gonna see here, it'll speed up, is 2026, the latter half of the years, you'll start to see the re-emergence of platform first for Veritone, right? Okay. Which really hasn't been the case for several years, right? On media and entertainment. No. I'm gonna say I think media and entertainment will still be dominated by applications. Okay. You'll see probably the biggest emergence in utilization of platform direct on, in the Fed space. Okay. More like a Palantir, right? If anybody's familiar with AIP and what they've been successful with. However, we're trying to do it without the requirement for four deployed engineers. We're trying to make it where it's more of a self-service type of platform and framework as compared to being, I'd say, overly SI or consultative based when you're doing an implementation at the platform level. Got it. Okay. Yeah. Helpful clarification there. All right, the most interesting incremental data point to me today from the earnings call was around the data hub and expanding the TAM with more customer opportunities there. What are you doing exactly to expand the number of customer opportunities with that from a product and customer perspective? What he's referring to is for the Masters, for example, in NCAA, the application built on aiWARE, the application they're using is called Digital Media Hub. That was primarily designed for, frankly, the largest entertainment shops, meaning the integration or the ingestion layer was done almost MAM to MAM, Media Asset Management system to it. Think of as enterprise grade. It was never really designed for self-service, smaller creators, enterprises who have lots of audio and video. You know, Lowe's department stores that the theme here now is everybody in effect is a media company. Everybody is producing audio and video at scale. We were missing out on that business line. Meaning for those who wanted more of a self-service approach, they wanted a lower cost entry point. That's something we've been working on now for a few months. Thankfully, it's not a huge lift, but you're gonna see us emerging over the next couple of months and reintroducing Digital Media Hub to, really, I'd say, reimagined in terms of onboarding, reimagined in terms of a price point, and reimagined in terms of an architecture, so we can go after those who have a few thousand dollars a year budget and not somebody who only has six figures or higher. We think that's gonna greatly open up, a large, you know, TAM for us in a big way, and I think we'll start to see the realization of some of those revenues as early as Q3. How do you go about the go-to-market for that dynamic? 'Cause right, you're historically, other than the public sector side, maybe you chase larger- Yeah you know, media companies, right? How do you manage that kind of dynamic there? Thankfully, there's a little bit of pent-up demand because, for example, the Big Ten and the Pac-12, I don't know what they are these days, but I think they're getting close to the Pac-12. They have teams. These properties have been wanting to do business with us for a while, but we really weren't built to go after smaller properties. First of all, I think, you know, is, I would say, is the affiliated organizations around these large conferences, if you talk about golf, there's the Players Direct. There's smaller tournaments that we've had to walk away from that we haven't really had the opportunity with. The Masters is such a large property. The amount of content they produce kind of crosses that bar where we could service them. I think number one is there is an installed pent-up backlog demand for us, by introducing, I'd say, this, I'm not gonna say lower end. It's got the same quality, it's got the same sophistication, but it really, the packaging and the price points allow us to go after them. The second one would be, is gonna be more net new to us, is corporate enterprises. These are, you know, groups that have marketing departments with a tremendous amount of audio and video. This one will be more net new to us, right? A reimagining, new go-to markets. I'll do the third one is partner. Partnership ecosystem, which I think we've done a pretty good job at, historically, is gonna be, we're really gonna rely on, which we're gonna touch on a little bit later here, the Oracles of the world, right? New partnerships that we've recently entered into who are trying to get very aggressive, trying to get more people to put, you know, both storage and compute payloads on OCI or Oracle Cloud Infrastructure. We are gonna be reselling with organizations like this, and we wanna make sure that we can go after everybody who's got audio and video payloads, not just media and entertainment, sports, and news enterprises. Got it. All right. On the public sector side, maybe still hitting on that, you've done a really good job with the OSI in rolling out the Air Force contract there. What's the background there, and how should we think about other opportunities within U.S. Federal? Patience is what you need when you go from commercial into the Fed. We're in a time of war, and so, and we're not selling tip-of-the-spear munitions, so things, let's just say, take a little bit longer. I think we signed the Air Force contract almost two years ago now. This is how long it kinda takes. The OSI, the Office of Special Investigations, is the division of the Air Force, which by the way, covers across other agencies as well. They're like the global policing force for everything. Whether it's security cameras going on bases, if they're doing active investigations, protecting their own or doing prosecutions, right, that are somehow affiliated with the global Department of War. Think of them frankly as a really big police agency or law enforcement agency. Again, we sign that contract. For them, the security requirements are a whole different level. We had to take the entire aiWARE stack and all the applications and deploy it in their private cloud. This is not something that's not running in AWS or Azure Gov or Commercial. This is actually in FedRAMP and also in air-gap, network-isolated environments. That was a big task. It forced us from a maturity effort. We had to kind of reimagine some aspects of the aiWARE platform, so we could actually deploy the full stack into these network-isolated environments. It's taken us a while, but Air Force and OSI is fully active. We expect them independently to continue to grow. We do think 2026 you'll start to see a ramp in direct revenues and expansion and utilization of services from the Air Force direct. Over time, the OSI and that body that's managing these services is been tasked to consolidate these efforts across the 17 Department of War agencies. Why this is so critical to Veritone is it's the land and double expand. It's the land and Air Force and growing that singular account, but it's also writing and helping support OSI, the Office of Special Investigations, as they deploy these type of solutions across, the goal is all other 17 Department of War agencies. That's a very important win. Just give you time perspective, you're talking about years before you start to see the revenue. The good news is, I don't care what side of the aisle you're on or change in, I'll say, the White House administration, hopefully these, what I like to say is the middle-tier back office solution where really we're landing is something that I think this could be literally a 20+ year relationship that's gonna grow and grow. That's awesome. All right. Also on the public sector side, you're working with, is it L.A. County or the LAPD? I wasn't quite sure who the customer is there. What can you tell us about your work with this customer? Yeah The use cases involved? We won't go into press release. We're working with both, LAPD and L.A. Sheriff's. It's a good setup. What's really interesting is we landed with them using completely different applications. One, in effect, launched with programmatic AI-based redaction, the other one launched with our investigative solution called Investigate. Built on the exact same aiWARE stack, with the budgets that they had, the entry point, we were able to land in, I'm not gonna give you specifics, one of the entities, they had the budgets for approval. We got into, we entered the relationship with a price point that we didn't have to wait for city council approval, right? We can be flexible with what app to land, and that's the application that one of these entities is using for investigative purposes. This is collect all the data. Can I find or association of that person wearing the blue jacket may have been associated with the 1983 blue Honda Civic with a dent, right? Can I follow them? You know, ultimately, can I zero in on the suspect or exonerate them quickly to ultimately close the case faster? On the flip side, the other L.A. entity onboarded with Redact first. This is pure autonomous redaction, audio, video, and document redaction of all the tonnage of information they're doing. As we all know, by all this stuff is accessible through Freedom of Information Acts, right? If we're recording it, right, whether it's if it's in effect citizen or taxpayer funded, those datasets eventually have to be released to the public. Some have to go through more formal process. Veritone Redact, which has won lots of awards, is definitely best of breed, makes that process incredibly more efficient. You're talking about something that's saving, you know, up to 90% efficiency in terms of speed of trying to prepare those files to get them out. That's a great example where you may run into a large agency that may not be open to throwing out their entire full stack, but they have the budgets to start working with you because if we can convince them that we have a best of breed of an investigation solution or redaction solution, that's how you land, right? That's a good example. All right. Let's make sure we hit on the OCI, stuff going on there. Maybe can you give us a little background on, you know, why did it make sense to partner with them? Yeah How you see the agreement going forward? We've tried to be completely agnostic from an infrastructure deployment perspective from the beginning. Like many, when we first speed to our MVP, I think we were initially on AWS commercial only. As we continue to rearchitect aiWARE, containerize a lot of the processes, purge ourselves from a lot of the legacy managed services that a lot of the, that the hyperscalers provide, that then opened us to move into GovCloud. That opened up the opportunity to move over to Azure. Frankly, if a customer wants us, we want to deliver the application and the platform wherever they want it hosted, to be very clear. We don't want that to be an inhibitor. When we looked at, and really this pushed us to the next level when we looked at FedRAMP. If you're not familiar with FedRAMP, that's again, the government's private cloud or just say another level of security. You can, by the way, be in FedRAMP. They have instances of Azure, Google Cloud, Oracle, AWS. Right now, we're also now in FedRAMP. First of all, us being technically ready to be completely platform-agnostic opened the door for us to start doing more stuff, more business with Oracle. Oracle, over the last few years, as you can imagine, I'd say the Oracle family in a greater sense has been pushing very hard in competing effectively with the AWS's and the Azures out there. With certain family members, when they got really aggressive in terms of buying Paramount and now merging with Warner Bros., Oracle is pushing very aggressively to compete direct in terms of scale and full in scope with the AWS's of the world. I would say it's mutual. We were fascinated by the allure of running our storage and compute cycles for cheaper, right, on Oracle. We were well aware that Oracle, in terms of worldwide points of their infrastructure around the world was second to none. I mean, if you wanted to go from any class of security and you're thinking about going to the U.K. or to Saudi, Oracle's been there for a long time from an Oracle Cloud perspective. Frankly, we just didn't feel, you know, we were quite ready to work with them on, frankly, our core businesses here in the United States. Again, they've improved and matured a ton, I think it was just kind of a mutual wooing phase that ultimately culminated in us getting this deal done. Yes, Veritone is going to be It's not exclusive, but we are gonna be looking at them as a premier, a preferred cloud provider. We are initially gonna be moving a lot of our commercial storage and payloads over to OCI over the next, you know, year and a half. The benefits of that is will be, A, definitively major cost savings on a run rate basis, to be clear. They're making this, they're creating great incentives for Veritone to be very competitive. By the way, this is gonna transfer not just to help improve our margins, that's gonna flow through our customer base. Purely on a cost basis, this is a big win. Number two, their performance is second to none. In terms of our benchmarking of how we're deploying our software in these environments, we've seen stellar results that are competitive at the worst case and in other areas more competitive in terms of performance of how we're preparing a lot of these data sets to execute our business. That's number two. Third, which is probably the most exciting for just growth, you're gonna start to see, you know, I'd say very acute, and short-term co-selling together with them. I will be speaking in their sales kickoff meeting in June, right, to thousands of salespeople, right? Talking about what we're doing and why. Big question: Why are you gonna choose to move your payloads onto OCI, right? One of the reasons is, well, now you can get Veritone, right, on OCI. You're gonna see really the three-prong. Highly incentivized to get us to start moving payloads, run rate performance and price advantage. Three, I'd say a very effective co-selling, relationship with them. Awesome. Great summary there. All right, the Veritone Hire business, it's, you know, been performing well in what's been a pretty difficult operating environment. What have you been doing on the product front there to distinguish the offering from others in the market? Broadbean's been around for, geez, almost 15+ years or more. Ubiquitous. Thousands of customers, if you think of, you know, talent acquisition and wanting to place, you know, job advertising across thousands of job boards, Broadbean has been there for a long time. It's an old stack. What we've been doing is reimagining the good and bad is they have a tremendous amount of data. I mean, you're talking about nearly 50,000, somewhere on average between 30,000 and 50,000 unique recruiters every month use their software to manage and place job ads at over 7,000 boards. Their data is incredible. It's also been very consistent. If you're trying to think about what an agentic reimagining of their solution is, there's nothing better than starting with that level of data set, right? The actions they're taking. What we've been doing is in effect taking, and it will be introduced by a project called Tao and then the new job management, set of modules, that is really bringing an agentic, layer across that that's gonna make those tasks, even though they've been relatively efficient, it's gonna take those tasks that those recruiters have to do on a day in and day out basis almost completely automating it. That coupled with our scale, is really I think gonna be very competitive against anybody in the market. To prove the point, and kind of the on the go-to-market side is, because of not just what we have been doing, but part of that roadmap is, we've resigned and expanded the type of relationships with some of the largest HCM providers out there, Workday, Oracle, SAP. Our fastest sales growth channel for our hiring business today is Workday referrals. We actually are, quote, unquote or whatever you call it, a gold standard, whatever, the gold level partner with Workday, which means they are selling our solutions, and we have a direct integration with Workday. I think that's, it's kind of the combination of us improving the product, having a AI agentic, you know, first approach and a roadmap, and then leveraging very effectively the largest players in the space who are co-selling with us. Got it. All right. In terms of the cost cuts implied in today's announcement, it's about $25 million-$30 million on an annualized basis, going forward. Really more starting next year on a full run rate basis. Why is now the right time to make these cuts and refocus the company a bit more? Veritone today has, I'd say, a certain percentage of our revenues is relatively very stable. It's like our baseline run rate with, I'll say, you know, kind of almost locked in, secure, you know, growth and, and X margin. And I'm not gonna give you that exact breakout. VDR, which is an exciting new lines of business, and even the Fed, they're hard to forecast. VDR, Veritone Data Refinery, unlike our SaaS subscription-based businesses, is all consumption-based. When we do a deal with Meta, there is no subscription monthly or quarterly or annual. It's literally they have a demand, we have to prepare datasets. These the size of these deals are, at the lower end, six figures, some of them, on average, seven figures. Relative to our revenue base, right, it's a huge swing. What we've decided to do, and I'll tell you why it's the right time and why we can do it now, is why are we chasing our losses so much? We have a great operating business. We have killer accounts, right? We have great entry points in public safety. We are going to reduce our baseline operating expense by up to 30% to get us that close to profitability even when revenues are moderate in our baseline business. What I mean by that is, when we do deliver the VDR and I'd say some of the more challenging to time when Air Force and some of these government contracts will ramp, we don't really care. We've corrected our right size of our cost structure. Therefore, we can reap the benefits on the outsized returns when the variable revenue happens. Why we can do it now is, first of all, we've been talking a lot about the technology platform. Pretty much all of our applications now are, I would say, on K8s. It's not to get too technical. We finally have transitioned everything to Kubernetes across the board. We're a lot more efficient in terms of the platform and the application layer. We can be much more efficient on how we're managing the applications and the entire infrastructure. We're finally at a point of maturity where you're gonna see more consolidation in sales and marketing and G&A. To be clear, we are not doing anything that in any way is gonna impede or impair our ability for growth or in any way impair our ability to drive these new exciting lines of businesses. This is, I would say, almost obligatory based upon what we've been able to do. I'm not gonna say it's way overdue, but I think it's time for us to introduce these things to bring that cost structure down. Awesome. All right. Well, with that, I think we can call it a day. I wanna thank Ryan and Veritone. Yeah for the time today. Thank you. Thank you. Appreciate it.

Speaker 1: Afternoon, and welcome to the Needham Technology, & Media Conference. This afternoon we're excited to have Veritone, with CEO Ryan Steelberg. Afternoon, and welcome to the Needham Technology, & Media Conference. afternoon and welcome to the needham technology & media conference This afternoon we're excited to have Veritone, with CEO Ryan Steelberg. this afternoon we're excited to have veritone with ceo ryan steelberg

Speaker 2: Hey, Josh. Great to be here. Hey, Josh. hey josh Great to be here. great to be here

Speaker 1: Yeah. All right. Ryan, maybe we can start with an overview of Veritone for those less familiar and the transformation that you've accomplished in the business over the last couple years. Yeah. yeah All right. all right Ryan, maybe we can start with an overview of Veritone for those less familiar and the transformation that you've accomplished in the business over the last couple years. ryan maybe we can start with an overview of veritone for those less familiar and the transformation that you've accomplished in the business over the last couple years

Speaker 2: Well, Veritone's been around a little over 10 years. We were kind of one of the first AI-based companies to really go after the unstructured data market. I come from a media entertainment ad tech background, and we felt that there was a gonna be a huge problem of the creation of a lot of unstructured data. If you kind of think about what Google and other search engines of the past did with structured data and text and HTML, we had a vision of what if you can ingest and start to index and understand all this audio and video. I came from Google. That was my job working for Sheryl Sandberg and Tim Armstrong, was: How can we start to understand what's inside audio/video? Primarily, to frankly sell more advertising space. We spun off. Well, Veritone's been around a little over 10 years. well veritone's been around a little over 10 years We were kind of one of the first AI-based companies to really go after the unstructured data market. we were kind of one of the first ai-based companies to really go after the unstructured data market I come from a media entertainment ad tech background, and we felt that there was a gonna be a huge problem of the creation of a lot of unstructured data. i come from a media entertainment ad tech background and we felt that there was a gonna be a huge problem of the creation of a lot of unstructured data If you kind of think about what Google and other search engines of the past did with structured data and text and HTML, we had a vision of what if you can ingest and start to index and understand all this audio and video. if you kind of think about what google and other search engines of the past did with structured data and text and html we had a vision of what if you can ingest and start to index and understand all this audio and video I came from Google. i came from google That was my job working for Sheryl Sandberg and Tim Armstrong, was: How can we start to understand what's inside audio/video? that was my job working for sheryl sandberg and tim armstrong was how can we start to understand what's inside audio/video Primarily, to frankly sell more advertising space. primarily to frankly sell more advertising space We spun off. we spun off The vision of Veritone was imagine a world where any type of audio and video, whether it's streaming audio, it's television, it's security cameras, if we can index all this audio and video, we could really unlock a lot of value and efficiencies across the board. Started the business in 2014. We still work with many of our original customers in the media entertainment space, and we've expanded a lot into public sector, state and local law enforcement. We work for the Department of War. We've been doing that for a while. One problem when you start really early is when we were kind of waiting for, I'd say, the AI market to mature, we did get a little fragmented as a business. We started to go into many different lines of business, going back several years. The vision of Veritone was imagine a world where any type of audio and video, whether it's streaming audio, it's television, it's security cameras, if we can index all this audio and video, we could really unlock a lot of value and efficiencies across the board. the vision of veritone was imagine a world where any type of audio and video whether it's streaming audio it's television it's security cameras if we can index all this audio and video we could really unlock a lot of value and efficiencies across the board Started the business in 2014. started the business in 2014 We still work with many of our original customers in the media entertainment space, and we've expanded a lot into public sector, state and local law enforcement. we still work with many of our original customers in the media entertainment space and we've expanded a lot into public sector state and local law enforcement We work for the Department of War. we work for the department of war We've been doing that for a while. we've been doing that for a while One problem when you start really early is when we were kind of waiting for, I'd say, the AI market to mature, we did get a little fragmented as a business. one problem when you start really early is when we were kind of waiting for i'd say the ai market to mature we did get a little fragmented as a business We started to go into many different lines of business, going back several years. we started to go into many different lines of business going back several years It really for us, over the last few years, was just getting back to our roots, our original thesis of can we just service, you know, our media entertainment customers, our police agencies, our Air Force customers, with, I would say, singular focus and that's what we've done. In addition to that, which you can kinda read by some of our filings, is, you know, we did have a lot of debt in the past, where, you know, we've paid off a lot of it, and we're down about $45 million of total debt, down from a peak of over $230 million of debt. It really for us, over the last few years, was just getting back to our roots, our original thesis of can we just service, you know, our media entertainment customers, our police agencies, our Air Force customers, with, I would say, singular focus and that's what we've done. it really for us over the last few years was just getting back to our roots our original thesis of can we just service you know our media entertainment customers our police agencies our air force customers with i would say singular focus and that's what we've done In addition to that, which you can kinda read by some of our filings, is, you know, we did have a lot of debt in the past, where, you know, we've paid off a lot of it, and we're down about $45 million of total debt, down from a peak of over $230 million of debt. in addition to that which you can kinda read by some of our filings is you know we did have a lot of debt in the past where you know we've paid off a lot of it and we're down about $45 million of total debt down from a peak of over $230 million of debt I think you're looking at Veritone as kind of a Although it's a lot of the same people, I'm still here, it's kind of a renewed focus, a renewed vision, and a much better balance sheet and, I'll say, fiscal responsibility. I think you're looking at Veritone as kind of a Although it's a lot of the same people, I'm still here, it's kind of a renewed focus, a renewed vision, and a much better balance sheet and, I'll say, fiscal responsibility. i think you're looking at veritone as kind of a although it's a lot of the same people i'm still here it's kind of a renewed focus a renewed vision and a much better balance sheet and i'll say fiscal responsibility

Speaker 1: Got it. Along with that, you spun off the advertising business. Got it. got it Along with that, you spun off the advertising business. along with that you spun off the advertising business

Speaker 2: Yeah Yeah yeah

Speaker 1: I guess, how long ago was that now? 18 months ago? I guess, how long ago was that now? 18 months ago? i guess how long ago was that now 18 months ago

Speaker 2: Well, Yeah, that was in Q4 2024. Part of it was, you know, again, there was just some peripheral businesses that I think were impeding some of our growth, which we've kind of shedded those, and now we're kind of back to our kinda core AI software business. Well, Yeah, that was in Q4 2024. well yeah that was in q4 2024 Part of it was, you know, again, there was just some peripheral businesses that I think were impeding some of our growth, which we've kind of shedded those, and now we're kind of back to our kinda core AI software business. part of it was you know again there was just some peripheral businesses that i think were impeding some of our growth which we've kind of shedded those and now we're kind of back to our kinda core ai software business

Speaker 1: Got it. All right. You just reported Q1 this morning, and obviously now we're here doing a fireside chat. Maybe to catch people up on the quarter, what would you say were some of the key highlights from the Q1 results? Got it. got it All right. all right You just reported Q1 this morning, and obviously now we're here doing a fireside chat. you just reported q1 this morning and obviously now we're here doing a fireside chat Maybe to catch people up on the quarter, what would you say were some of the key highlights from the Q1 results? maybe to catch people up on the quarter what would you say were some of the key highlights from the q1 results

Speaker 2: I think first of all was, you know, revenue was relatively flat year-over-year. I think the big highlights for us was a huge expansion in our pipeline for some of our new data lines of business called VDR, Veritone Data Refinery. We're gonna talk a little bit about that in the future. We did announce some very key signings of two mega new clients of ours, Google and NVIDIA, where we are now, I'd say, a Tier 1 partner of theirs, helping prepare, package and license training data to them, somewhat akin to like a Scale AI, if you're familiar with that business. That's definitely another highlight. And I think a third is just the velocity and growth of our public safety business. I think first of all was, you know, revenue was relatively flat year-over-year. i think first of all was you know revenue was relatively flat year-over-year I think the big highlights for us was a huge expansion in our pipeline for some of our new data lines of business called VDR, Veritone Data Refinery. i think the big highlights for us was a huge expansion in our pipeline for some of our new data lines of business called vdr veritone data refinery We're gonna talk a little bit about that in the future. we're gonna talk a little bit about that in the future We did announce some very key signings of two mega new clients of ours, Google and NVIDIA, where we are now, I'd say, a Tier 1 partner of theirs, helping prepare, package and license training data to them, somewhat akin to like a Scale AI, if you're familiar with that business. we did announce some very key signings of two mega new clients of ours google and nvidia where we are now i'd say a tier 1 partner of theirs helping prepare package and license training data to them somewhat akin to like a scale ai if you're familiar with that business That's definitely another highlight. that's definitely another highlight And I think a third is just the velocity and growth of our public safety business. and i think a third is just the velocity and growth of our public safety business 69% year-over-year on a quarterly basis in terms of growth. You know, new activation with the Air Force and the Defense Logistics Agency, which we'll go into. I think it was a combination of, again, just improvements of operational efficiency, expansion of the pipeline, and thankfully landing, which we're probably about a quarter overdue, some of them are more bellwether contract with Google and NVIDIA. 69% year-over-year on a quarterly basis in terms of growth. 69% year-over-year on a quarterly basis in terms of growth You know, new activation with the Air Force and the Defense Logistics Agency, which we'll go into. you know new activation with the air force and the defense logistics agency which we'll go into I think it was a combination of, again, just improvements of operational efficiency, expansion of the pipeline, and thankfully landing, which we're probably about a quarter overdue, some of them are more bellwether contract with Google and NVIDIA. i think it was a combination of again just improvements of operational efficiency expansion of the pipeline and thankfully landing which we're probably about a quarter overdue some of them are more bellwether contract with google and nvidia

Speaker 1: Got it. All right. VDR obviously is, kinda the key upswing factor in your business model right now. Maybe you could just start off by explaining what do you do with this VDR platform, and maybe why is it differentiated versus your competitors? Got it. got it All right. all right VDR obviously is, kinda the key upswing factor in your business model right now. vdr obviously is kinda the key upswing factor in your business model right now Maybe you could just start off by explaining what do you do with this VDR platform, and maybe why is it differentiated versus your competitors? maybe you could just start off by explaining what do you do with this vdr platform and maybe why is it differentiated versus your competitors

Speaker 2: Veritone Data Refinery, for 10 years, we have been ingesting and indexing tens of millions of hours of audio and video for our customers. Those range from CBS News to the Masters Tournament to security camera footage. Organically, about two years ago, we really start to see how a lot of the large hyperscaler companies who are building foundational models, the OpenAIs of the world, the Geminis, they really started to need a tremendous amount of clean, IP-cleared audio and video for training data. Obviously, these models were originally trained on primarily text. They've advanced to imagery, now audio and video and other forms of unstructured data. Veritone organically has been processing and indexing this audio and video dataset for years. Veritone Data Refinery, for 10 years, we have been ingesting and indexing tens of millions of hours of audio and video for our customers. veritone data refinery for 10 years we have been ingesting and indexing tens of millions of hours of audio and video for our customers Those range from CBS News to the Masters Tournament to security camera footage. those range from cbs news to the masters tournament to security camera footage Organically, about two years ago, we really start to see how a lot of the large hyperscaler companies who are building foundational models, the OpenAIs of the world, the Geminis, they really started to need a tremendous amount of clean, IP-cleared audio and video for training data. organically about two years ago we really start to see how a lot of the large hyperscaler companies who are building foundational models the openais of the world the geminis they really started to need a tremendous amount of clean ip-cleared audio and video for training data Obviously, these models were originally trained on primarily text. obviously these models were originally trained on primarily text They've advanced to imagery, now audio and video and other forms of unstructured data. they've advanced to imagery now audio and video and other forms of unstructured data Veritone organically has been processing and indexing this audio and video dataset for years. veritone organically has been processing and indexing this audio and video dataset for years We made the decision to introduce that new line of business, named the Veritone Data Refinery, then we've started to package and start to license those datasets to many of the largest hyperscalers out there. We're thrilled about it. We're very excited about it. What makes us really unique is, first, I would say, you know, our expertise in understanding the audio and video datasets. It's probably second to none. That's really where we cut our teeth. We made the decision to introduce that new line of business, named the Veritone Data Refinery, then we've started to package and start to license those datasets to many of the largest hyperscalers out there. we made the decision to introduce that new line of business named the veritone data refinery then we've started to package and start to license those datasets to many of the largest hyperscalers out there We're thrilled about it. we're thrilled about it We're very excited about it. we're very excited about it What makes us really unique is, first, I would say, you know, our expertise in understanding the audio and video datasets. what makes us really unique is first i would say you know our expertise in understanding the audio and video datasets It's probably second to none. it's probably second to none That's really where we cut our teeth. that's really where we cut our teeth You kind of say if you think of AI and audio and video understanding and indexing, I think that's really where Veritone shines for a multitude of reasons, scale, efficiency, and frankly the end, I'd say the output of our processing to prepare the datasets for AI-based processing. The second is our supply. As Mike, our CFO, touched on in our earnings, we've been signing a tremendous amount of supply with partners to the tunes of, you know, 50 million hours of plus of data that we're able to now leverage and introduce those datasets to hyperscalers. You kind of say if you think of AI and audio and video understanding and indexing, I think that's really where Veritone shines for a multitude of reasons, scale, efficiency, and frankly the end, I'd say the output of our processing to prepare the datasets for AI-based processing. you kind of say if you think of ai and audio and video understanding and indexing i think that's really where veritone shines for a multitude of reasons scale efficiency and frankly the end i'd say the output of our processing to prepare the datasets for ai-based processing The second is our supply. the second is our supply As Mike, our CFO, touched on in our earnings, we've been signing a tremendous amount of supply with partners to the tunes of, you know, 50 million hours of plus of data that we're able to now leverage and introduce those datasets to hyperscalers. as mike our cfo touched on in our earnings we've been signing a tremendous amount of supply with partners to the tunes of you know 50 million hours of plus of data that we're able to now leverage and introduce those datasets to hyperscalers We've created, in effect, a kind of a multi-tier moat here, a huge repository of proprietary data assets to prepare and license. That we have now also signed, which we also announced, is really almost every single foundational model player, that are also under contract. We sit on both sides. We have a representation agreement with supply. Now we have signed contracts on the VDR side with all the buyers. We're in a fantastic situation finally to start, let's say, you know, sprinting and executing on the VDR business. We've created, in effect, a kind of a multi-tier moat here, a huge repository of proprietary data assets to prepare and license. we've created in effect a kind of a multi-tier moat here a huge repository of proprietary data assets to prepare and license That we have now also signed, which we also announced, is really almost every single foundational model player, that are also under contract. that we have now also signed which we also announced is really almost every single foundational model player that are also under contract We sit on both sides. we sit on both sides We have a representation agreement with supply. we have a representation agreement with supply Now we have signed contracts on the VDR side with all the buyers. now we have signed contracts on the vdr side with all the buyers We're in a fantastic situation finally to start, let's say, you know, sprinting and executing on the VDR business. we're in a fantastic situation finally to start let's say you know sprinting and executing on the vdr business

Speaker 1: Maybe just to touch on, you know, what makes it difficult to index and make unstructured data searchable? Is there something inherent in the way that the data is, like, put together that makes it difficult? How have you kinda like, you know, overcome that, the difficulties with that? Maybe just to touch on, you know, what makes it difficult to index and make unstructured data searchable? maybe just to touch on you know what makes it difficult to index and make unstructured data searchable Is there something inherent in the way that the data is, like, put together that makes it difficult? is there something inherent in the way that the data is like put together that makes it difficult How have you kinda like, you know, overcome that, the difficulties with that? how have you kinda like you know overcome that the difficulties with that

Speaker 2: I think, well, first is the scale. When, you know, understanding audio and video, obviously the models are getting more mature. Typically, when you see a lot of these use cases, you're dealing with minutes or a few hours of content, candidly. When you're talking about archives that have hundreds of thousands or even millions of hours, that is a tremendous amount of processing, and frankly, expense. When you're thinking about trying to prepare datasets for large language models, they don't need just a couple hundred hours. Often, they need thousands or tens of thousands or hundreds of thousands of hours. I think, well, first is the scale. i think well first is the scale When, you know, understanding audio and video, obviously the models are getting more mature. when you know understanding audio and video obviously the models are getting more mature Typically, when you see a lot of these use cases, you're dealing with minutes or a few hours of content, candidly. typically when you see a lot of these use cases you're dealing with minutes or a few hours of content candidly When you're talking about archives that have hundreds of thousands or even millions of hours, that is a tremendous amount of processing, and frankly, expense. when you're talking about archives that have hundreds of thousands or even millions of hours that is a tremendous amount of processing and frankly expense When you're thinking about trying to prepare datasets for large language models, they don't need just a couple hundred hours. when you're thinking about trying to prepare datasets for large language models they don't need just a couple hundred hours Often, they need thousands or tens of thousands or hundreds of thousands of hours. often they need thousands or tens of thousands or hundreds of thousands of hours This is as much, I'll call, an orchestration dealing with the details of bitrate and quality and performance of the video files themselves, as much as it is leveraging the cognitive science of turning that into structured data with temporal metadata. I think it's, for Veritone, it's the combination of both expertise on the underlying aspects of audio and video, going back a very long time of understanding audio and video in the media and entertainment space, coupled with our expertise in I'll call cognitive AI, that combination has proven to be very effective in servicing, frankly, the highest demanding customers out there, which are the hyperscalers. One other thing to note is when we prepare these datasets for the different, aforementioned customers, they all want it slightly different, right? This is as much, I'll call, an orchestration dealing with the details of bitrate and quality and performance of the video files themselves, as much as it is leveraging the cognitive science of turning that into structured data with temporal metadata. this is as much i'll call an orchestration dealing with the details of bitrate and quality and performance of the video files themselves as much as it is leveraging the cognitive science of turning that into structured data with temporal metadata I think it's, for Veritone, it's the combination of both expertise on the underlying aspects of audio and video, going back a very long time of understanding audio and video in the media and entertainment space, coupled with our expertise in I'll call cognitive AI, that combination has proven to be very effective in servicing, frankly, the highest demanding customers out there, which are the hyperscalers. i think it's for veritone it's the combination of both expertise on the underlying aspects of audio and video going back a very long time of understanding audio and video in the media and entertainment space coupled with our expertise in i'll call cognitive ai that combination has proven to be very effective in servicing frankly the highest demanding customers out there which are the hyperscalers One other thing to note is when we prepare these datasets for the different, aforementioned customers, they all want it slightly different, right? one other thing to note is when we prepare these datasets for the different aforementioned customers they all want it slightly different right Don't think of it as just us transferring a video file over. There's a lot of work that we have to do and prepare it differently for company A, like a Meta, versus somebody else, like an AWS. Don't think of it as just us transferring a video file over. don't think of it as just us transferring a video file over There's a lot of work that we have to do and prepare it differently for company A, like a Meta, versus somebody else, like an AWS. there's a lot of work that we have to do and prepare it differently for company a like a meta versus somebody else like an aws

Speaker 1: Got it. Okay. Super helpful. All right. If we look at the VDR opportunity, it seems like the near-term kinda major revenue opportunities remain with the largest hyperscalers. Is that the case, and how does that dynamic factor into the implied, second half, ramp in revenue based on your guidance? Got it. got it Okay. okay Super helpful. super helpful All right. all right If we look at the VDR opportunity, it seems like the near-term kinda major revenue opportunities remain with the largest hyperscalers. if we look at the vdr opportunity it seems like the near-term kinda major revenue opportunities remain with the largest hyperscalers Is that the case, and how does that dynamic factor into the implied, second half, ramp in revenue based on your guidance? is that the case and how does that dynamic factor into the implied second half ramp in revenue based on your guidance

Speaker 2: I mean, you think we read in the press, right? The largest budgets that are funding this huge infrastructure build-out are these large hyperscalers, right? The data investment into data training sense is no different, right? What we did project is we do expect for this year at a minimum, the super majority of our revenues from the VDR are gonna come from these largest hyperscalers. That being said, because the cost of compute, the cost of storage, and I'll say the efficiencies of a lot of the AI models or the ability to train models, that bar is coming down. We are seeing an expansion of the type and number of customers. I mean, you think we read in the press, right? i mean you think we read in the press right The largest budgets that are funding this huge infrastructure build-out are these large hyperscalers, right? the largest budgets that are funding this huge infrastructure build-out are these large hyperscalers right The data investment into data training sense is no different, right? the data investment into data training sense is no different right What we did project is we do expect for this year at a minimum, the super majority of our revenues from the VDR are gonna come from these largest hyperscalers. what we did project is we do expect for this year at a minimum the super majority of our revenues from the vdr are gonna come from these largest hyperscalers That being said, because the cost of compute, the cost of storage, and I'll say the efficiencies of a lot of the AI models or the ability to train models, that bar is coming down. that being said because the cost of compute the cost of storage and i'll say the efficiencies of a lot of the ai models or the ability to train models that bar is coming down We are seeing an expansion of the type and number of customers. we are seeing an expansion of the type and number of customers Yeah, and don't wanna drop, you know, some names, but let's just say that you wouldn't readily think that they're in the business now of training AI models. To be clear, at least for 2026, it's gonna be dominated by the Metas of the world and the AWSs of the world. Yeah, and don't wanna drop, you know, some names, but let's just say that you wouldn't readily think that they're in the business now of training AI models. yeah and don't wanna drop you know some names but let's just say that you wouldn't readily think that they're in the business now of training ai models To be clear, at least for 2026, it's gonna be dominated by the Metas of the world and the AWSs of the world. to be clear at least for 2026 it's gonna be dominated by the metas of the world and the awss of the world

Speaker 1: Got it. All right. Then maybe just to wrap up that point, the implied second half ramp and the revenue, what gives you kinda confidence in terms of what you're seeing behind the scenes to make sense that there is gonna be some upward trajectory to that revenue? We may not know the-precise dynamic, but- Got it. got it All right. all right Then maybe just to wrap up that point, the implied second half ramp and the revenue, what gives you kinda confidence in terms of what you're seeing behind the scenes to make sense that there is gonna be some upward trajectory to that revenue? then maybe just to wrap up that point the implied second half ramp and the revenue what gives you kinda confidence in terms of what you're seeing behind the scenes to make sense that there is gonna be some upward trajectory to that revenue We may not know the- precise dynamic, but- we may not know the- precise dynamic but-

Speaker 2: I think, well, two keys is one, some of the supply we've been talking about, was recently just signed, right? As, you know, let's say as late Q4. The amount of data that we have access to prepare, to package, to sell has greatly increased by stuff that was recently bought on board under contract in late Q4. Think of it as much more supply. Number two is, as we've just touched on, two of the biggest players in the entire space didn't even come under contract until late February. I think, well, two keys is one, some of the supply we've been talking about, was recently just signed, right? i think well two keys is one some of the supply we've been talking about was recently just signed right As, you know, let's say as late Q4. as you know let's say as late q4 The amount of data that we have access to prepare, to package, to sell has greatly increased by stuff that was recently bought on board under contract in late Q4. the amount of data that we have access to prepare to package to sell has greatly increased by stuff that was recently bought on board under contract in late q4 Think of it as much more supply. think of it as much more supply Number two is, as we've just touched on, two of the biggest players in the entire space didn't even come under contract until late February. number two is as we've just touched on two of the biggest players in the entire space didn't even come under contract until late february

Speaker 1: Right. Right. right

Speaker 2: If you kinda look at those two huge components in terms of fuel, right, or limiting factors, those have been sort of satisfied. The third element is, which we touched on, is our near-term pipeline is almost $70 million now for VDR, with a material amount of that already out for a quote, if you will, for booking. I think it's just, we were talking about such a compressed period of time here of semantics of a few weeks. If you kinda project that forward, we're very bullish on what that pipeline looks like and how we're gonna be able to mobilize that pipeline through 2026. If you kinda look at those two huge components in terms of fuel, right, or limiting factors, those have been sort of satisfied. if you kinda look at those two huge components in terms of fuel right or limiting factors those have been sort of satisfied The third element is, which we touched on, is our near-term pipeline is almost $70 million now for VDR, with a material amount of that already out for a quote, if you will, for booking. the third element is which we touched on is our near-term pipeline is almost $70 million now for vdr with a material amount of that already out for a quote if you will for booking I think it's just, we were talking about such a compressed period of time here of semantics of a few weeks. i think it's just we were talking about such a compressed period of time here of semantics of a few weeks If you kinda project that forward, we're very bullish on what that pipeline looks like and how we're gonna be able to mobilize that pipeline through 2026. if you kinda project that forward we're very bullish on what that pipeline looks like and how we're gonna be able to mobilize that pipeline through 2026

Speaker 1: Got it. That's super helpful. All right. You have an open platform approach where customers can bring in any third-party AI models. Can you explain why that's the right product strategy versus a closed-loop system, some of your competitors pursue? Maybe on top of that, are some of the competitors that did have closed-loop systems adjusting their approach? Got it. got it That's super helpful. that's super helpful All right. all right You have an open platform approach where customers can bring in any third-party AI models. you have an open platform approach where customers can bring in any third-party ai models Can you explain why that's the right product strategy versus a closed-loop system, some of your competitors pursue? can you explain why that's the right product strategy versus a closed-loop system some of your competitors pursue Maybe on top of that, are some of the competitors that did have closed-loop systems adjusting their approach? maybe on top of that are some of the competitors that did have closed-loop systems adjusting their approach

Speaker 2: Yeah Yeah yeah

Speaker 1: because they realized it was a mistake? because they realized it was a mistake? because they realized it was a mistake

Speaker 2: Let me reset for the audience in here. We're not talking about necessarily VDR anymore. Let me reset for the audience in here. let me reset for the audience in here We're not talking about necessarily VDR anymore. we're not talking about necessarily vdr anymore

Speaker 1: Yes Yes yes

Speaker 2: Let's go back to how I'm servicing ESPN, right? If I'm ingesting all of ESPN's content from all these different sources, we build bespoke recipes of different AI and cognition to turn it into structured metadata. Question would be, okay, great, you know, there's, you know, at the, you know, three years ago, we were using, let's say, a fine-tuned transcription model that's good for global English, hypothetically. If you, in this space, the one thing that's always constant is change, okay? It's a little cliché, but every single day, we're not seeing more innovation as it relates to models. Not just large language models, not just large multimodality models, but bespoke models like object detection, face detection, et cetera. Let's go back to how I'm servicing ESPN, right? let's go back to how i'm servicing espn right If I'm ingesting all of ESPN's content from all these different sources, we build bespoke recipes of different AI and cognition to turn it into structured metadata. if i'm ingesting all of espn's content from all these different sources we build bespoke recipes of different ai and cognition to turn it into structured metadata Question would be, okay, great, you know, there's, you know, at the, you know, three years ago, we were using, let's say, a fine-tuned transcription model that's good for global English, hypothetically. If you, in this space, the one thing that's always constant is change, okay? question would be okay great you know there's you know at the you know three years ago we were using let's say a fine-tuned transcription model that's good for global english hypothetically. if you in this space the one thing that's always constant is change okay It's a little cliché, but every single day, we're not seeing more innovation as it relates to models. it's a little cliché but every single day we're not seeing more innovation as it relates to models Not just large language models, not just large multimodality models, but bespoke models like object detection, face detection, et cetera. not just large language models not just large multimodality models but bespoke models like object detection face detection et cetera From day one, our thesis was, and this goes back all the way to 2014, was we made a bet that there was gonna be millions of models, right? I'm not gonna say we were clairvoyant in saying that we were gonna see the, necessarily the large language models, but what you're seeing today, right, is we're still seeing better efficiency and accuracy for hyper-trained, narrow cognitive models for certain things, like finding a Honda Accord 1983 with a blue dent in the back. That can be trained, right? I don't know why you're grinning. Maybe it was the car that you stole. Working in concert, well, I'll say with general understanding of video, that could be more appropriate with a large video-based model. From day one, our thesis was, and this goes back all the way to 2014, was we made a bet that there was gonna be millions of models, right? from day one our thesis was and this goes back all the way to 2014 was we made a bet that there was gonna be millions of models right I'm not gonna say we were clairvoyant in saying that we were gonna see the, necessarily the large language models, but what you're seeing today, right, is we're still seeing better efficiency and accuracy for hyper-trained, narrow cognitive models for certain things, like finding a Honda Accord 1983 with a blue dent in the back. i'm not gonna say we were clairvoyant in saying that we were gonna see the necessarily the large language models but what you're seeing today right is we're still seeing better efficiency and accuracy for hyper-trained narrow cognitive models for certain things like finding a honda accord 1983 with a blue dent in the back That can be trained, right? that can be trained right I don't know why you're grinning. i don't know why you're grinning Maybe it was the car that you stole. maybe it was the car that you stole Working in concert, well, I'll say with general understanding of video, that could be more appropriate with a large video-based model. working in concert well i'll say with general understanding of video that could be more appropriate with a large video-based model

Speaker 1: Yeah. Yeah. yeah

Speaker 2: What we've seen time and time again is when you can blend these art forms, you get the both worlds. You get the best accuracy, and you can do it at phenomenal price. Remember, a lot of the data that we're talking about, the volume is so big, and a lot of it can't leave our environment. I can't take our video, for example, from ESPN or take our data from a police investigation and necessarily load it into a publicly hosted large model. Okay? First of all, I'm not even allowed to move it often, right? The datasets. Or two, the volume is so big that if you kinda look at the cost of the tokens and the processing for these, it'd be cost prohibitive. I'd be spending tens of millions of dollars a year just to create the metadata. What we've seen time and time again is when you can blend these art forms, you get the both worlds. what we've seen time and time again is when you can blend these art forms you get the both worlds You get the best accuracy, and you can do it at phenomenal price. you get the best accuracy and you can do it at phenomenal price Remember, a lot of the data that we're talking about, the volume is so big, and a lot of it can't leave our environment. remember a lot of the data that we're talking about the volume is so big and a lot of it can't leave our environment I can't take our video, for example, from ESPN or take our data from a police investigation and necessarily load it into a publicly hosted large model. i can't take our video for example from espn or take our data from a police investigation and necessarily load it into a publicly hosted large model Okay? okay First of all, I'm not even allowed to move it often, right? first of all i'm not even allowed to move it often right The datasets. the datasets Or two, the volume is so big that if you kinda look at the cost of the tokens and the processing for these, it'd be cost prohibitive. or two the volume is so big that if you kinda look at the cost of the tokens and the processing for these it'd be cost prohibitive I'd be spending tens of millions of dollars a year just to create the metadata. i'd be spending tens of millions of dollars a year just to create the metadata Our job is, without ruining the application or the workflow experience, if there's a better model on the market, our goal is to get it onboarded as a hosted, a containerized model onto the aiWARE stack, which is our proprietary stack, as quickly as possible. One thing to note is roughly about 30% of the models that we've invoked over the last, like for example, 24 months, are Veritone's proprietary trained models, right? Meaning we don't care, right? If there's a better model that has better yield, better productivity, we wanna have that onboarded onto our stack as quickly as possible without disrupting the customer's experience at all. Our job is, without ruining the application or the workflow experience, if there's a better model on the market, our goal is to get it onboarded as a hosted, a containerized model onto the aiWARE stack, which is our proprietary stack, as quickly as possible. our job is without ruining the application or the workflow experience if there's a better model on the market our goal is to get it onboarded as a hosted a containerized model onto the aiware stack which is our proprietary stack as quickly as possible One thing to note is roughly about 30% of the models that we've invoked over the last, like for example, 24 months, are Veritone's proprietary trained models, right? one thing to note is roughly about 30% of the models that we've invoked over the last like for example 24 months are veritone's proprietary trained models right Meaning we don't care, right? meaning we don't care right If there's a better model that has better yield, better productivity, we wanna have that onboarded onto our stack as quickly as possible without disrupting the customer's experience at all. if there's a better model that has better yield better productivity we wanna have that onboarded onto our stack as quickly as possible without disrupting the customer's experience at all

Speaker 1: Got it. All right. In terms of the public safety, part of your business, how do you continue to build awareness with customers of your position in the marketplace, while at the same time work within customer budgets to kinda get a foot in the door? Got it. got it All right. all right In terms of the public safety, part of your business, how do you continue to build awareness with customers of your position in the marketplace, while at the same time work within customer budgets to kinda get a foot in the door? in terms of the public safety part of your business how do you continue to build awareness with customers of your position in the marketplace while at the same time work within customer budgets to kinda get a foot in the door

Speaker 2: We'll break this into two parts. We'll do SLED, state and local law enforcement, and kind of federal government. In state and local law enforcement, there's a few legacy titan players. Axon is a major player. Flock is a major player. Motorola is a major player. What we're seeing is a lot of these groups come in as almost a vertical stack. Vendor lock-in is something that's scary to everybody. This is a real issue. And also the price points that a lot of these legacy companies are coming to bear are very expensive. Police agencies, sheriff departments, municipalities are under major budget constraints. If you take the culmination of, frankly, us coming in later with, I'd say, an open platform framework that we can use with any data source, right, any type of player, it's fascinating. We'll break this into two parts. we'll break this into two parts We'll do SLED, state and local law enforcement, and kind of federal government. we'll do sled state and local law enforcement and kind of federal government In state and local law enforcement, there's a few legacy titan players. in state and local law enforcement there's a few legacy titan players Axon is a major player. axon is a major player Flock is a major player. flock is a major player Motorola is a major player. motorola is a major player What we're seeing is a lot of these groups come in as almost a vertical stack. what we're seeing is a lot of these groups come in as almost a vertical stack Vendor lock-in is something that's scary to everybody. vendor lock-in is something that's scary to everybody This is a real issue. this is a real issue And also the price points that a lot of these legacy companies are coming to bear are very expensive. and also the price points that a lot of these legacy companies are coming to bear are very expensive Police agencies, sheriff departments, municipalities are under major budget constraints. police agencies sheriff departments municipalities are under major budget constraints If you take the culmination of, frankly, us coming in later with, I'd say, an open platform framework that we can use with any data source, right, any type of player, it's fascinating. if you take the culmination of frankly us coming in later with i'd say an open platform framework that we can use with any data source right any type of player it's fascinating The best way I can describe it is almost 40% of our current customer base is also an Axon customer. They're also a Motorola customer. What I mean by that is Veritone sits on top. Think of it as a data abstraction layer that sits on top of any deployed infrastructure. I don't care where, what body camera, platform they have. I don't care what CCTV or drone provider they have. The key is for us to come in very cost effectively and create that intelligence data layer on top. The goal here is I wanna solve crime faster, right? I wanna be able to ingest the data from any cell phone, from any CCTV camera, and if I can help that investigator move that case along and increase their case closure rate faster, everybody wins. The best way I can describe it is almost 40% of our current customer base is also an Axon customer. the best way i can describe it is almost 40% of our current customer base is also an axon customer They're also a Motorola customer. they're also a motorola customer What I mean by that is Veritone sits on top. what i mean by that is veritone sits on top Think of it as a data abstraction layer that sits on top of any deployed infrastructure. think of it as a data abstraction layer that sits on top of any deployed infrastructure I don't care where, what body camera, platform they have. i don't care where what body camera platform they have I don't care what CCTV or drone provider they have. i don't care what cctv or drone provider they have The key is for us to come in very cost effectively and create that intelligence data layer on top. the key is for us to come in very cost effectively and create that intelligence data layer on top The goal here is I wanna solve crime faster, right? the goal here is i wanna solve crime faster right I wanna be able to ingest the data from any cell phone, from any CCTV camera, and if I can help that investigator move that case along and increase their case closure rate faster, everybody wins. i wanna be able to ingest the data from any cell phone from any cctv camera and if i can help that investigator move that case along and increase their case closure rate faster everybody wins The other byproduct is they don't have to necessarily be over-reliant or basically take, at times, inferior solutions. I would say is our end applications, our redaction software, our investigation software is best of breed. We can compete against anybody, and so therefore, we are encouraging working with with the cities directly and with other competitors, other body camera companies, et cetera, as a, I'll say a partner horizontal complementor. Do we wanna provide the LAPD with the best of breed solution end to end? They shouldn't be forced to take a vertical lock-in that's overpriced and frankly has stuff that's an inferior product. The other byproduct is they don't have to necessarily be over-reliant or basically take, at times, inferior solutions. the other byproduct is they don't have to necessarily be over-reliant or basically take at times inferior solutions I would say is our end applications, our redaction software, our investigation software is best of breed. i would say is our end applications our redaction software our investigation software is best of breed We can compete against anybody, and so therefore, we are encouraging working with with the cities directly and with other competitors, other body camera companies, et cetera, as a, I'll say a partner horizontal complementor. we can compete against anybody and so therefore we are encouraging working with with the cities directly and with other competitors other body camera companies et cetera as a i'll say a partner horizontal complementor Do we wanna provide the LAPD with the best of breed solution end to end? do we wanna provide the lapd with the best of breed solution end to end They shouldn't be forced to take a vertical lock-in that's overpriced and frankly has stuff that's an inferior product. they shouldn't be forced to take a vertical lock-in that's overpriced and frankly has stuff that's an inferior product

Speaker 1: Got it. All right. As you think about the future product roadmap for public sector, how are you thinking about selling just the straight platform to customers versus selling individual applications? Maybe explaining that might be helpful. Got it. got it All right. all right As you think about the future product roadmap for public sector, how are you thinking about selling just the straight platform to customers versus selling individual applications? as you think about the future product roadmap for public sector how are you thinking about selling just the straight platform to customers versus selling individual applications Maybe explaining that might be helpful. maybe explaining that might be helpful

Speaker 2: Right now, our core stack is called aiWARE. Every application we build for commercial, like the ESPNs or the applications or workflows we build for the federal government or state and local law enforcement, are built on top of aiWARE. The majority of our revenue is actually being derived from us licensing and them using those end applications. Think of it as Windows versus Microsoft Office, right? Everybody knows that Windows and other operating systems have SDKs. You can build your own proprietary applications on those. By the way, you can do the same thing with aiWARE. Far, we've had the most success of selling our applications. Right now, our core stack is called aiWARE. right now our core stack is called aiware Every application we build for commercial, like the ESPNs or the applications or workflows we build for the federal government or state and local law enforcement, are built on top of aiWARE. every application we build for commercial like the espns or the applications or workflows we build for the federal government or state and local law enforcement are built on top of aiware The majority of our revenue is actually being derived from us licensing and them using those end applications. the majority of our revenue is actually being derived from us licensing and them using those end applications Think of it as Windows versus Microsoft Office, right? think of it as windows versus microsoft office right Everybody knows that Windows and other operating systems have SDKs. everybody knows that windows and other operating systems have sdks You can build your own proprietary applications on those. you can build your own proprietary applications on those By the way, you can do the same thing with aiWARE. by the way you can do the same thing with aiware Far, we've had the most success of selling our applications. far we've had the most success of selling our applications What we are seeing, and I think that's going to be case for smaller agencies, right, who have limited technical resources or budgets, we don't envision them building necessarily custom applications or solutions today on aiWARE. The larger agencies, yes, because their use cases are more diversified, they're more complicated, and frankly, they have so many different departments that us reimagining what a, an improved workflow or a custom application for like, let's say, LAPD, makes a lot of sense, right? Versus you force-feeding them, right, I say a smaller or limited scope application. Very simply is I do see us still being more successful selling applications, AI-based applications to smaller firms. Larger firms, you'll start to see more custom builds and solutions built on aiWARE, which is what we're seeing in the Fed. What we are seeing, and I think that's going to be case for smaller agencies, right, who have limited technical resources or budgets, we don't envision them building necessarily custom applications or solutions today on aiWARE. what we are seeing and i think that's going to be case for smaller agencies right who have limited technical resources or budgets we don't envision them building necessarily custom applications or solutions today on aiware The larger agencies, yes, because their use cases are more diversified, they're more complicated, and frankly, they have so many different departments that us reimagining what a, an improved workflow or a custom application for like, let's say, LAPD, makes a lot of sense, right? the larger agencies yes because their use cases are more diversified they're more complicated and frankly they have so many different departments that us reimagining what a an improved workflow or a custom application for like let's say lapd makes a lot of sense right Versus you force-feeding them, right, I say a smaller or limited scope application. versus you force-feeding them right i say a smaller or limited scope application Very simply is I do see us still being more successful selling applications, AI-based applications to smaller firms. very simply is i do see us still being more successful selling applications ai-based applications to smaller firms Larger firms, you'll start to see more custom builds and solutions built on aiWARE, which is what we're seeing in the Fed. larger firms you'll start to see more custom builds and solutions built on aiware which is what we're seeing in the fed U.S. Senate, the Air Force, Defense Logistics Agency, by the way, they all started with buying single applications. Every one of those clients now are building or frankly at times engaging us to build custom workflows and applications. Not just taking the off the shelf applications, but doing something that's larger or more custom for their type of organization. U.S. u.s Senate, the Air Force, Defense Logistics Agency, by the way, they all started with buying single applications. senate the air force defense logistics agency by the way they all started with buying single applications Every one of those clients now are building or frankly at times engaging us to build custom workflows and applications. every one of those clients now are building or frankly at times engaging us to build custom workflows and applications Not just taking the off the shelf applications, but doing something that's larger or more custom for their type of organization. not just taking the off the shelf applications but doing something that's larger or more custom for their type of organization

Speaker 1: How does that compare to your kind of historical kind of dominance or strength in the media and entertainment vertical where you were just selling the platform? Why did it make sense for you, for those customers primarily to buy the platform and not build individual applications for those customers? How does that compare to your kind of historical kind of dominance or strength in the media and entertainment vertical where you were just selling the platform? how does that compare to your kind of historical kind of dominance or strength in the media and entertainment vertical where you were just selling the platform Why did it make sense for you, for those customers primarily to buy the platform and not build individual applications for those customers? why did it make sense for you for those customers primarily to buy the platform and not build individual applications for those customers

Speaker 2: Well, actually, we have, we very rarely ever sold just the platform in the past to media and entertainment. Well, actually, we have, we very rarely ever sold just the platform in the past to media and entertainment. well actually we have we very rarely ever sold just the platform in the past to media and entertainment

Speaker 1: Okay. Okay. okay

Speaker 2: It's almost always been the application layer, right? Of selling into media and entertainment, right? Very rarely were they buying, for example, Maybe if the first couple years, with like Disney and a couple others, we were simply, they were accessing our APIs and building custom solutions on top of that. That was not very successful in 2014 through 2018. It was too early in the space. It's kinda like, people didn't have a webmaster back in the day, right? Even though you could build very easy websites in HTML, people frankly just wanted turnkey applications back then. It's almost always been the application layer, right? it's almost always been the application layer right Of selling into media and entertainment, right? of selling into media and entertainment right Very rarely were they buying, for example, Maybe if the first couple years, with like Disney and a couple others, we were simply, they were accessing our APIs and building custom solutions on top of that. very rarely were they buying for example maybe if the first couple years with like disney and a couple others we were simply they were accessing our apis and building custom solutions on top of that That was not very successful in 2014 through 2018. that was not very successful in 2014 through 2018 It was too early in the space. it was too early in the space It's kinda like, people didn't have a webmaster back in the day, right? it's kinda like people didn't have a webmaster back in the day right Even though you could build very easy websites in HTML, people frankly just wanted turnkey applications back then. even though you could build very easy websites in html people frankly just wanted turnkey applications back then Just to be clear, what gave us all the benefit was thankfully the way we designed the workflow and the SDK of aiWARE afforded us the ability to build these applications so cost effectively, right? That are very competitive or extensible. What you're gonna see here, it'll speed up, is 2026, the latter half of the years, you'll start to see the re-emergence of platform first for Veritone, right? Just to be clear, what gave us all the benefit was thankfully the way we designed the workflow and the SDK of aiWARE afforded us the ability to build these applications so cost effectively, right? just to be clear what gave us all the benefit was thankfully the way we designed the workflow and the sdk of aiware afforded us the ability to build these applications so cost effectively right That are very competitive or extensible. that are very competitive or extensible What you're gonna see here, it'll speed up, is 2026, the latter half of the years, you'll start to see the re-emergence of platform first for Veritone, right? what you're gonna see here it'll speed up is 2026 the latter half of the years you'll start to see the re-emergence of platform first for veritone right

Speaker 1: Okay. Okay. okay

Speaker 2: Which really hasn't been the case for several years, right? Which really hasn't been the case for several years, right? which really hasn't been the case for several years right

Speaker 1: On media and entertainment. On media and entertainment. on media and entertainment

Speaker 2: No. I'm gonna say I think media and entertainment will still be dominated by applications. No. no I'm gonna say I think media and entertainment will still be dominated by applications. i'm gonna say i think media and entertainment will still be dominated by applications

Speaker 1: Okay. Okay. okay

Speaker 2: You'll see probably the biggest emergence in utilization of platform direct on, in the Fed space. You'll see probably the biggest emergence in utilization of platform direct on, in the Fed space. you'll see probably the biggest emergence in utilization of platform direct on in the fed space

Speaker 1: Okay. Okay. okay

Speaker 2: More like a Palantir, right? If anybody's familiar with AIP and what they've been successful with. However, we're trying to do it without the requirement for four deployed engineers. We're trying to make it where it's more of a self-service type of platform and framework as compared to being, I'd say, overly SI or consultative based when you're doing an implementation at the platform level. More like a Palantir, right? more like a palantir right If anybody's familiar with AIP and what they've been successful with. if anybody's familiar with aip and what they've been successful with However, we're trying to do it without the requirement for four deployed engineers. however we're trying to do it without the requirement for four deployed engineers We're trying to make it where it's more of a self-service type of platform and framework as compared to being, I'd say, overly SI or consultative based when you're doing an implementation at the platform level. we're trying to make it where it's more of a self-service type of platform and framework as compared to being i'd say overly si or consultative based when you're doing an implementation at the platform level

Speaker 1: Got it. Okay. Got it. got it Okay. okay

Speaker 2: Yeah. Yeah. yeah

Speaker 1: Helpful clarification there. All right, the most interesting incremental data point to me today from the earnings call was around the data hub and expanding the TAM with more customer opportunities there. What are you doing exactly to expand the number of customer opportunities with that from a product and customer perspective? Helpful clarification there. helpful clarification there All right, the most interesting incremental data point to me today from the earnings call was around the data hub and expanding the TAM with more customer opportunities there. all right the most interesting incremental data point to me today from the earnings call was around the data hub and expanding the tam with more customer opportunities there What are you doing exactly to expand the number of customer opportunities with that from a product and customer perspective? what are you doing exactly to expand the number of customer opportunities with that from a product and customer perspective

Speaker 2: What he's referring to is for the Masters, for example, in NCAA, the application built on aiWARE, the application they're using is called Digital Media Hub. That was primarily designed for, frankly, the largest entertainment shops, meaning the integration or the ingestion layer was done almost MAM to MAM, Media Asset Management system to it. Think of as enterprise grade. It was never really designed for self-service, smaller creators, enterprises who have lots of audio and video. You know, Lowe's department stores that the theme here now is everybody in effect is a media company. Everybody is producing audio and video at scale. We were missing out on that business line. Meaning for those who wanted more of a self-service approach, they wanted a lower cost entry point. What he's referring to is for the Masters, for example, in NCAA, the application built on aiWARE, the application they're using is called Digital Media Hub. what he's referring to is for the masters for example in ncaa the application built on aiware the application they're using is called digital media hub That was primarily designed for, frankly, the largest entertainment shops, meaning the integration or the ingestion layer was done almost MAM to MAM, Media Asset Management system to it. that was primarily designed for frankly the largest entertainment shops meaning the integration or the ingestion layer was done almost mam to mam media asset management system to it Think of as enterprise grade. think of as enterprise grade It was never really designed for self-service, smaller creators, enterprises who have lots of audio and video. it was never really designed for self-service smaller creators enterprises who have lots of audio and video You know, Lowe's department stores that the theme here now is everybody in effect is a media company. you know lowe's department stores that the theme here now is everybody in effect is a media company Everybody is producing audio and video at scale. everybody is producing audio and video at scale We were missing out on that business line. we were missing out on that business line Meaning for those who wanted more of a self-service approach, they wanted a lower cost entry point. meaning for those who wanted more of a self-service approach they wanted a lower cost entry point That's something we've been working on now for a few months. Thankfully, it's not a huge lift, but you're gonna see us emerging over the next couple of months and reintroducing Digital Media Hub to, really, I'd say, reimagined in terms of onboarding, reimagined in terms of a price point, and reimagined in terms of an architecture, so we can go after those who have a few thousand dollars a year budget and not somebody who only has six figures or higher. We think that's gonna greatly open up, a large, you know, TAM for us in a big way, and I think we'll start to see the realization of some of those revenues as early as Q3. That's something we've been working on now for a few months. that's something we've been working on now for a few months Thankfully, it's not a huge lift, but you're gonna see us emerging over the next couple of months and reintroducing Digital Media Hub to, really, I'd say, reimagined in terms of onboarding, reimagined in terms of a price point, and reimagined in terms of an architecture, so we can go after those who have a few thousand dollars a year budget and not somebody who only has six figures or higher. thankfully it's not a huge lift but you're gonna see us emerging over the next couple of months and reintroducing digital media hub to really i'd say reimagined in terms of onboarding reimagined in terms of a price point and reimagined in terms of an architecture so we can go after those who have a few thousand dollars a year budget and not somebody who only has six figures or higher We think that's gonna greatly open up, a large, you know, TAM for us in a big way, and I think we'll start to see the realization of some of those revenues as early as Q3. we think that's gonna greatly open up a large you know tam for us in a big way and i think we'll start to see the realization of some of those revenues as early as q3

Speaker 1: How do you go about the go-to-market for that dynamic? 'Cause right, you're historically, other than the public sector side, maybe you chase larger- How do you go about the go-to-market for that dynamic? 'Cause right, you're historically, other than the public sector side, maybe you chase larger- how do you go about the go-to-market for that dynamic 'cause right you're historically other than the public sector side maybe you chase larger-

Speaker 2: Yeah Yeah yeah

Speaker 1: you know, media companies, right? How do you manage that kind of dynamic there? you know, media companies, right? you know media companies right How do you manage that kind of dynamic there? how do you manage that kind of dynamic there

Speaker 2: Thankfully, there's a little bit of pent-up demand because, for example, the Big Ten and the Pac-12, I don't know what they are these days, but I think they're getting close to the Pac-12. They have teams. These properties have been wanting to do business with us for a while, but we really weren't built to go after smaller properties. First of all, I think, you know, is, I would say, is the affiliated organizations around these large conferences, if you talk about golf, there's the Players Direct. There's smaller tournaments that we've had to walk away from that we haven't really had the opportunity with. The Masters is such a large property. The amount of content they produce kind of crosses that bar where we could service them. Thankfully, there's a little bit of pent-up demand because, for example, the Big Ten and the Pac-12, I don't know what they are these days, but I think they're getting close to the Pac-12. thankfully there's a little bit of pent-up demand because for example the big ten and the pac-12 i don't know what they are these days but i think they're getting close to the pac-12 They have teams. they have teams These properties have been wanting to do business with us for a while, but we really weren't built to go after smaller properties. these properties have been wanting to do business with us for a while but we really weren't built to go after smaller properties First of all, I think, you know, is, I would say, is the affiliated organizations around these large conferences, if you talk about golf, there's the Players Direct. first of all i think you know is i would say is the affiliated organizations around these large conferences if you talk about golf there's the players direct There's smaller tournaments that we've had to walk away from that we haven't really had the opportunity with. there's smaller tournaments that we've had to walk away from that we haven't really had the opportunity with The Masters is such a large property. the masters is such a large property The amount of content they produce kind of crosses that bar where we could service them. the amount of content they produce kind of crosses that bar where we could service them I think number one is there is an installed pent-up backlog demand for us, by introducing, I'd say, this, I'm not gonna say lower end. It's got the same quality, it's got the same sophistication, but it really, the packaging and the price points allow us to go after them. The second one would be, is gonna be more net new to us, is corporate enterprises. These are, you know, groups that have marketing departments with a tremendous amount of audio and video. This one will be more net new to us, right? A reimagining, new go-to markets. I'll do the third one is partner. I think number one is there is an installed pent-up backlog demand for us, by introducing, I'd say, this, I'm not gonna say lower end. i think number one is there is an installed pent-up backlog demand for us by introducing i'd say this i'm not gonna say lower end It's got the same quality, it's got the same sophistication, but it really, the packaging and the price points allow us to go after them. it's got the same quality it's got the same sophistication but it really the packaging and the price points allow us to go after them The second one would be, is gonna be more net new to us, is corporate enterprises. the second one would be is gonna be more net new to us is corporate enterprises These are, you know, groups that have marketing departments with a tremendous amount of audio and video. these are you know groups that have marketing departments with a tremendous amount of audio and video This one will be more net new to us, right? this one will be more net new to us right A reimagining, new go-to markets. a reimagining new go-to markets I'll do the third one is partner. i'll do the third one is partner Partnership ecosystem, which I think we've done a pretty good job at, historically, is gonna be, we're really gonna rely on, which we're gonna touch on a little bit later here, the Oracles of the world, right? New partnerships that we've recently entered into who are trying to get very aggressive, trying to get more people to put, you know, both storage and compute payloads on OCI or Oracle Cloud Infrastructure. We are gonna be reselling with organizations like this, and we wanna make sure that we can go after everybody who's got audio and video payloads, not just media and entertainment, sports, and news enterprises. Partnership ecosystem, which I think we've done a pretty good job at, historically, is gonna be, we're really gonna rely on, which we're gonna touch on a little bit later here, the Oracles of the world, right? partnership ecosystem which i think we've done a pretty good job at historically is gonna be we're really gonna rely on which we're gonna touch on a little bit later here the oracles of the world right New partnerships that we've recently entered into who are trying to get very aggressive, trying to get more people to put, you know, both storage and compute payloads on OCI or Oracle Cloud Infrastructure. new partnerships that we've recently entered into who are trying to get very aggressive trying to get more people to put you know both storage and compute payloads on oci or oracle cloud infrastructure We are gonna be reselling with organizations like this, and we wanna make sure that we can go after everybody who's got audio and video payloads, not just media and entertainment, sports, and news enterprises. we are gonna be reselling with organizations like this and we wanna make sure that we can go after everybody who's got audio and video payloads not just media and entertainment sports and news enterprises

Speaker 1: Got it. All right. On the public sector side, maybe still hitting on that, you've done a really good job with the OSI in rolling out the Air Force contract there. What's the background there, and how should we think about other opportunities within U.S. Federal? Got it. got it All right. all right On the public sector side, maybe still hitting on that, you've done a really good job with the OSI in rolling out the Air Force contract there. on the public sector side maybe still hitting on that you've done a really good job with the osi in rolling out the air force contract there What's the background there, and how should we think about other opportunities within U.S. what's the background there and how should we think about other opportunities within u.s Federal? federal

Speaker 2: Patience is what you need when you go from commercial into the Fed. We're in a time of war, and so, and we're not selling tip-of-the-spear munitions, so things, let's just say, take a little bit longer. I think we signed the Air Force contract almost two years ago now. This is how long it kinda takes. The OSI, the Office of Special Investigations, is the division of the Air Force, which by the way, covers across other agencies as well. They're like the global policing force for everything. Whether it's security cameras going on bases, if they're doing active investigations, protecting their own or doing prosecutions, right, that are somehow affiliated with the global Department of War. Think of them frankly as a really big police agency or law enforcement agency. Patience is what you need when you go from commercial into the Fed. patience is what you need when you go from commercial into the fed We're in a time of war, and so, and we're not selling tip-of-the-spear munitions, so things, let's just say, take a little bit longer. we're in a time of war and so and we're not selling tip-of-the-spear munitions so things let's just say take a little bit longer I think we signed the Air Force contract almost two years ago now. i think we signed the air force contract almost two years ago now This is how long it kinda takes. this is how long it kinda takes The OSI, the Office of Special Investigations, is the division of the Air Force, which by the way, covers across other agencies as well. the osi the office of special investigations is the division of the air force which by the way covers across other agencies as well They're like the global policing force for everything. they're like the global policing force for everything Whether it's security cameras going on bases, if they're doing active investigations, protecting their own or doing prosecutions, right, that are somehow affiliated with the global Department of War. whether it's security cameras going on bases if they're doing active investigations protecting their own or doing prosecutions right that are somehow affiliated with the global department of war Think of them frankly as a really big police agency or law enforcement agency. think of them frankly as a really big police agency or law enforcement agency Again, we sign that contract. For them, the security requirements are a whole different level. We had to take the entire aiWARE stack and all the applications and deploy it in their private cloud. This is not something that's not running in AWS or Azure Gov or Commercial. This is actually in FedRAMP and also in air-gap, network-isolated environments. That was a big task. It forced us from a maturity effort. We had to kind of reimagine some aspects of the aiWARE platform, so we could actually deploy the full stack into these network-isolated environments. It's taken us a while, but Air Force and OSI is fully active. We expect them independently to continue to grow. Again, we sign that contract. again we sign that contract For them, the security requirements are a whole different level. for them the security requirements are a whole different level We had to take the entire aiWARE stack and all the applications and deploy it in their private cloud. we had to take the entire aiware stack and all the applications and deploy it in their private cloud This is not something that's not running in AWS or Azure Gov or Commercial. this is not something that's not running in aws or azure gov or commercial This is actually in FedRAMP and also in air-gap, network-isolated environments. this is actually in fedramp and also in air-gap network-isolated environments That was a big task. that was a big task It forced us from a maturity effort. it forced us from a maturity effort We had to kind of reimagine some aspects of the aiWARE platform, so we could actually deploy the full stack into these network-isolated environments. we had to kind of reimagine some aspects of the aiware platform so we could actually deploy the full stack into these network-isolated environments It's taken us a while, but Air Force and OSI is fully active. it's taken us a while but air force and osi is fully active We expect them independently to continue to grow. we expect them independently to continue to grow We do think 2026 you'll start to see a ramp in direct revenues and expansion and utilization of services from the Air Force direct. Over time, the OSI and that body that's managing these services is been tasked to consolidate these efforts across the 17 Department of War agencies. Why this is so critical to Veritone is it's the land and double expand. It's the land and Air Force and growing that singular account, but it's also writing and helping support OSI, the Office of Special Investigations, as they deploy these type of solutions across, the goal is all other 17 Department of War agencies. That's a very important win. Just give you time perspective, you're talking about years before you start to see the revenue. We do think 2026 you'll start to see a ramp in direct revenues and expansion and utilization of services from the Air Force direct. we do think 2026 you'll start to see a ramp in direct revenues and expansion and utilization of services from the air force direct Over time, the OSI and that body that's managing these services is been tasked to consolidate these efforts across the 17 Department of War agencies. over time the osi and that body that's managing these services is been tasked to consolidate these efforts across the 17 department of war agencies Why this is so critical to Veritone is it's the land and double expand. why this is so critical to veritone is it's the land and double expand It's the land and Air Force and growing that singular account, but it's also writing and helping support OSI, the Office of Special Investigations, as they deploy these type of solutions across, the goal is all other 17 Department of War agencies. it's the land and air force and growing that singular account but it's also writing and helping support osi the office of special investigations as they deploy these type of solutions across the goal is all other 17 department of war agencies That's a very important win. that's a very important win Just give you time perspective, you're talking about years before you start to see the revenue. just give you time perspective you're talking about years before you start to see the revenue The good news is, I don't care what side of the aisle you're on or change in, I'll say, the White House administration, hopefully these, what I like to say is the middle-tier back office solution where really we're landing is something that I think this could be literally a 20+ year relationship that's gonna grow and grow. The good news is, I don't care what side of the aisle you're on or change in, I'll say, the White House administration, hopefully these, what I like to say is the middle-tier back office solution where really we're landing is something that I think this could be literally a 20+ year relationship that's gonna grow and grow. the good news is i don't care what side of the aisle you're on or change in i'll say the white house administration hopefully these what i like to say is the middle-tier back office solution where really we're landing is something that i think this could be literally a 20+ year relationship that's gonna grow and grow

Speaker 1: That's awesome. All right. Also on the public sector side, you're working with, is it L.A. County or the LAPD? I wasn't quite sure who the customer is there. What can you tell us about your work with this customer? That's awesome. that's awesome All right. all right Also on the public sector side, you're working with, is it L.A. also on the public sector side you're working with is it l.a County or the LAPD? county or the lapd I wasn't quite sure who the customer is there. i wasn't quite sure who the customer is there What can you tell us about your work with this customer? what can you tell us about your work with this customer

Speaker 2: Yeah Yeah yeah

Speaker 1: The use cases involved? The use cases involved? the use cases involved

Speaker 2: We won't go into press release. We're working with both, LAPD and L.A. Sheriff's. It's a good setup. What's really interesting is we landed with them using completely different applications. One, in effect, launched with programmatic AI-based redaction, the other one launched with our investigative solution called Investigate. Built on the exact same aiWARE stack, with the budgets that they had, the entry point, we were able to land in, I'm not gonna give you specifics, one of the entities, they had the budgets for approval. We got into, we entered the relationship with a price point that we didn't have to wait for city council approval, right? We won't go into press release. we won't go into press release We're working with both, LAPD and L.A. we're working with both lapd and l.a Sheriff's. sheriff's It's a good setup. it's a good setup What's really interesting is we landed with them using completely different applications. what's really interesting is we landed with them using completely different applications One, in effect, launched with programmatic AI-based redaction, the other one launched with our investigative solution called Investigate. one in effect launched with programmatic ai-based redaction the other one launched with our investigative solution called investigate Built on the exact same aiWARE stack, with the budgets that they had, the entry point, we were able to land in, I'm not gonna give you specifics, one of the entities, they had the budgets for approval. built on the exact same aiware stack with the budgets that they had the entry point we were able to land in i'm not gonna give you specifics one of the entities they had the budgets for approval We got into, we entered the relationship with a price point that we didn't have to wait for city council approval, right? we got into we entered the relationship with a price point that we didn't have to wait for city council approval right We can be flexible with what app to land, and that's the application that one of these entities is using for investigative purposes. This is collect all the data. Can I find or association of that person wearing the blue jacket may have been associated with the 1983 blue Honda Civic with a dent, right? Can I follow them? You know, ultimately, can I zero in on the suspect or exonerate them quickly to ultimately close the case faster? On the flip side, the other L.A. entity onboarded with Redact first. This is pure autonomous redaction, audio, video, and document redaction of all the tonnage of information they're doing. As we all know, by all this stuff is accessible through Freedom of Information Acts, right? We can be flexible with what app to land, and that's the application that one of these entities is using for investigative purposes. we can be flexible with what app to land and that's the application that one of these entities is using for investigative purposes This is collect all the data. this is collect all the data Can I find or association of that person wearing the blue jacket may have been associated with the 1983 blue Honda Civic with a dent, right? can i find or association of that person wearing the blue jacket may have been associated with the 1983 blue honda civic with a dent right Can I follow them? can i follow them You know, ultimately, can I zero in on the suspect or exonerate them quickly to ultimately close the case faster? you know ultimately can i zero in on the suspect or exonerate them quickly to ultimately close the case faster On the flip side, the other L.A. entity onboarded with Redact first. on the flip side the other l.a entity onboarded with redact first This is pure autonomous redaction, audio, video, and document redaction of all the tonnage of information they're doing. this is pure autonomous redaction audio video and document redaction of all the tonnage of information they're doing As we all know, by all this stuff is accessible through Freedom of Information Acts, right? as we all know by all this stuff is accessible through freedom of information acts right If we're recording it, right, whether it's if it's in effect citizen or taxpayer funded, those datasets eventually have to be released to the public. Some have to go through more formal process. Veritone Redact, which has won lots of awards, is definitely best of breed, makes that process incredibly more efficient. You're talking about something that's saving, you know, up to 90% efficiency in terms of speed of trying to prepare those files to get them out. That's a great example where you may run into a large agency that may not be open to throwing out their entire full stack, but they have the budgets to start working with you because if we can convince them that we have a best of breed of an investigation solution or redaction solution, that's how you land, right? That's a good example. If we're recording it, right, whether it's if it's in effect citizen or taxpayer funded, those datasets eventually have to be released to the public. if we're recording it right whether it's if it's in effect citizen or taxpayer funded those datasets eventually have to be released to the public Some have to go through more formal process. some have to go through more formal process Veritone Redact, which has won lots of awards, is definitely best of breed, makes that process incredibly more efficient. veritone redact which has won lots of awards is definitely best of breed makes that process incredibly more efficient You're talking about something that's saving, you know, up to 90% efficiency in terms of speed of trying to prepare those files to get them out. you're talking about something that's saving you know up to 90% efficiency in terms of speed of trying to prepare those files to get them out That's a great example where you may run into a large agency that may not be open to throwing out their entire full stack, but they have the budgets to start working with you because if we can convince them that we have a best of breed of an investigation solution or redaction solution, that's how you land, right? that's a great example where you may run into a large agency that may not be open to throwing out their entire full stack but they have the budgets to start working with you because if we can convince them that we have a best of breed of an investigation solution or redaction solution that's how you land right That's a good example. that's a good example

Speaker 1: All right. Let's make sure we hit on the OCI, stuff going on there. Maybe can you give us a little background on, you know, why did it make sense to partner with them? All right. all right Let's make sure we hit on the OCI, stuff going on there. let's make sure we hit on the oci stuff going on there Maybe can you give us a little background on, you know, why did it make sense to partner with them? maybe can you give us a little background on you know why did it make sense to partner with them

Speaker 2: Yeah Yeah yeah

Speaker 1: How you see the agreement going forward? How you see the agreement going forward? how you see the agreement going forward

Speaker 2: We've tried to be completely agnostic from an infrastructure deployment perspective from the beginning. Like many, when we first speed to our MVP, I think we were initially on AWS commercial only. As we continue to rearchitect aiWARE, containerize a lot of the processes, purge ourselves from a lot of the legacy managed services that a lot of the, that the hyperscalers provide, that then opened us to move into GovCloud. That opened up the opportunity to move over to Azure. Frankly, if a customer wants us, we want to deliver the application and the platform wherever they want it hosted, to be very clear. We don't want that to be an inhibitor. When we looked at, and really this pushed us to the next level when we looked at FedRAMP. We've tried to be completely agnostic from an infrastructure deployment perspective from the beginning. we've tried to be completely agnostic from an infrastructure deployment perspective from the beginning Like many, when we first speed to our MVP, I think we were initially on AWS commercial only. like many when we first speed to our mvp i think we were initially on aws commercial only As we continue to rearchitect aiWARE, containerize a lot of the processes, purge ourselves from a lot of the legacy managed services that a lot of the, that the hyperscalers provide, that then opened us to move into GovCloud. as we continue to rearchitect aiware containerize a lot of the processes purge ourselves from a lot of the legacy managed services that a lot of the that the hyperscalers provide that then opened us to move into govcloud That opened up the opportunity to move over to Azure. that opened up the opportunity to move over to azure Frankly, if a customer wants us, we want to deliver the application and the platform wherever they want it hosted, to be very clear. frankly if a customer wants us we want to deliver the application and the platform wherever they want it hosted to be very clear We don't want that to be an inhibitor. we don't want that to be an inhibitor When we looked at, and really this pushed us to the next level when we looked at FedRAMP. when we looked at and really this pushed us to the next level when we looked at fedramp If you're not familiar with FedRAMP, that's again, the government's private cloud or just say another level of security. You can, by the way, be in FedRAMP. They have instances of Azure, Google Cloud, Oracle, AWS. Right now, we're also now in FedRAMP. First of all, us being technically ready to be completely platform-agnostic opened the door for us to start doing more stuff, more business with Oracle. Oracle, over the last few years, as you can imagine, I'd say the Oracle family in a greater sense has been pushing very hard in competing effectively with the AWS's and the Azures out there. If you're not familiar with FedRAMP, that's again, the government's private cloud or just say another level of security. if you're not familiar with fedramp that's again the government's private cloud or just say another level of security You can, by the way, be in FedRAMP. you can by the way be in fedramp They have instances of Azure, Google Cloud, Oracle, AWS. they have instances of azure google cloud oracle aws Right now, we're also now in FedRAMP. First of all, us being technically ready to be completely platform-agnostic opened the door for us to start doing more stuff, more business with Oracle. right now we're also now in fedramp. first of all us being technically ready to be completely platform-agnostic opened the door for us to start doing more stuff more business with oracle Oracle, over the last few years, as you can imagine, I'd say the Oracle family in a greater sense has been pushing very hard in competing effectively with the AWS's and the Azures out there. oracle over the last few years as you can imagine i'd say the oracle family in a greater sense has been pushing very hard in competing effectively with the aws's and the azures out there With certain family members, when they got really aggressive in terms of buying Paramount and now merging with Warner Bros., Oracle is pushing very aggressively to compete direct in terms of scale and full in scope with the AWS's of the world. I would say it's mutual. We were fascinated by the allure of running our storage and compute cycles for cheaper, right, on Oracle. We were well aware that Oracle, in terms of worldwide points of their infrastructure around the world was second to none. I mean, if you wanted to go from any class of security and you're thinking about going to the U.K. or to Saudi, Oracle's been there for a long time from an Oracle Cloud perspective. With certain family members, when they got really aggressive in terms of buying Paramount and now merging with Warner Bros., Oracle is pushing very aggressively to compete direct in terms of scale and full in scope with the AWS's of the world. with certain family members when they got really aggressive in terms of buying paramount and now merging with warner bros oracle is pushing very aggressively to compete direct in terms of scale and full in scope with the aws's of the world I would say it's mutual. i would say it's mutual We were fascinated by the allure of running our storage and compute cycles for cheaper, right, on Oracle. we were fascinated by the allure of running our storage and compute cycles for cheaper right on oracle We were well aware that Oracle, in terms of worldwide points of their infrastructure around the world was second to none. we were well aware that oracle in terms of worldwide points of their infrastructure around the world was second to none I mean, if you wanted to go from any class of security and you're thinking about going to the U.K. or to Saudi, Oracle's been there for a long time from an Oracle Cloud perspective. i mean if you wanted to go from any class of security and you're thinking about going to the u.k or to saudi oracle's been there for a long time from an oracle cloud perspective Frankly, we just didn't feel, you know, we were quite ready to work with them on, frankly, our core businesses here in the United States. Again, they've improved and matured a ton, I think it was just kind of a mutual wooing phase that ultimately culminated in us getting this deal done. Yes, Veritone is going to be It's not exclusive, but we are gonna be looking at them as a premier, a preferred cloud provider. We are initially gonna be moving a lot of our commercial storage and payloads over to OCI over the next, you know, year and a half. The benefits of that is will be, A, definitively major cost savings on a run rate basis, to be clear. Frankly, we just didn't feel, you know, we were quite ready to work with them on, frankly, our core businesses here in the United States. frankly we just didn't feel you know we were quite ready to work with them on frankly our core businesses here in the united states Again, they've improved and matured a ton, I think it was just kind of a mutual wooing phase that ultimately culminated in us getting this deal done. again they've improved and matured a ton i think it was just kind of a mutual wooing phase that ultimately culminated in us getting this deal done Yes, Veritone is going to be It's not exclusive, but we are gonna be looking at them as a premier, a preferred cloud provider. yes veritone is going to be it's not exclusive but we are gonna be looking at them as a premier a preferred cloud provider We are initially gonna be moving a lot of our commercial storage and payloads over to OCI over the next, you know, year and a half. we are initially gonna be moving a lot of our commercial storage and payloads over to oci over the next you know year and a half The benefits of that is will be, A, definitively major cost savings on a run rate basis, to be clear. the benefits of that is will be a definitively major cost savings on a run rate basis to be clear They're making this, they're creating great incentives for Veritone to be very competitive. By the way, this is gonna transfer not just to help improve our margins, that's gonna flow through our customer base. Purely on a cost basis, this is a big win. Number two, their performance is second to none. In terms of our benchmarking of how we're deploying our software in these environments, we've seen stellar results that are competitive at the worst case and in other areas more competitive in terms of performance of how we're preparing a lot of these data sets to execute our business. That's number two. They're making this, they're creating great incentives for Veritone to be very competitive. they're making this they're creating great incentives for veritone to be very competitive By the way, this is gonna transfer not just to help improve our margins, that's gonna flow through our customer base. by the way this is gonna transfer not just to help improve our margins that's gonna flow through our customer base Purely on a cost basis, this is a big win. purely on a cost basis this is a big win Number two, their performance is second to none. number two their performance is second to none In terms of our benchmarking of how we're deploying our software in these environments, we've seen stellar results that are competitive at the worst case and in other areas more competitive in terms of performance of how we're preparing a lot of these data sets to execute our business. in terms of our benchmarking of how we're deploying our software in these environments we've seen stellar results that are competitive at the worst case and in other areas more competitive in terms of performance of how we're preparing a lot of these data sets to execute our business That's number two. that's number two Third, which is probably the most exciting for just growth, you're gonna start to see, you know, I'd say very acute, and short-term co-selling together with them. I will be speaking in their sales kickoff meeting in June, right, to thousands of salespeople, right? Talking about what we're doing and why. Big question: Why are you gonna choose to move your payloads onto OCI, right? One of the reasons is, well, now you can get Veritone, right, on OCI. You're gonna see really the three-prong. Highly incentivized to get us to start moving payloads, run rate performance and price advantage. Three, I'd say a very effective co-selling, relationship with them. Third, which is probably the most exciting for just growth, you're gonna start to see, you know, I'd say very acute, and short-term co-selling together with them. third which is probably the most exciting for just growth you're gonna start to see you know i'd say very acute and short-term co-selling together with them I will be speaking in their sales kickoff meeting in June, right, to thousands of salespeople, right? i will be speaking in their sales kickoff meeting in june right to thousands of salespeople right Talking about what we're doing and why. talking about what we're doing and why Big question: Why are you gonna choose to move your payloads onto OCI, right? big question why are you gonna choose to move your payloads onto oci right One of the reasons is, well, now you can get Veritone, right, on OCI. one of the reasons is well now you can get veritone right on oci You're gonna see really the three-prong. you're gonna see really the three-prong Highly incentivized to get us to start moving payloads, run rate performance and price advantage. highly incentivized to get us to start moving payloads run rate performance and price advantage Three, I'd say a very effective co-selling, relationship with them. three i'd say a very effective co-selling relationship with them

Speaker 1: Awesome. Great summary there. All right, the Veritone Hire business, it's, you know, been performing well in what's been a pretty difficult operating environment. What have you been doing on the product front there to distinguish the offering from others in the market? Awesome. awesome Great summary there. great summary there All right, the Veritone Hire business, it's, you know, been performing well in what's been a pretty difficult operating environment. all right the veritone hire business it's you know been performing well in what's been a pretty difficult operating environment What have you been doing on the product front there to distinguish the offering from others in the market? what have you been doing on the product front there to distinguish the offering from others in the market

Speaker 2: Broadbean's been around for, geez, almost 15+ years or more. Ubiquitous. Thousands of customers, if you think of, you know, talent acquisition and wanting to place, you know, job advertising across thousands of job boards, Broadbean has been there for a long time. It's an old stack. What we've been doing is reimagining the good and bad is they have a tremendous amount of data. I mean, you're talking about nearly 50,000, somewhere on average between 30,000 and 50,000 unique recruiters every month use their software to manage and place job ads at over 7,000 boards. Their data is incredible. It's also been very consistent. If you're trying to think about what an agentic reimagining of their solution is, there's nothing better than starting with that level of data set, right? Broadbean's been around for, geez, almost 15+ years or more. broadbean's been around for geez almost 15+ years or more Ubiquitous. ubiquitous Thousands of customers, if you think of, you know, talent acquisition and wanting to place, you know, job advertising across thousands of job boards, Broadbean has been there for a long time. thousands of customers if you think of you know talent acquisition and wanting to place you know job advertising across thousands of job boards broadbean has been there for a long time It's an old stack. it's an old stack What we've been doing is reimagining the good and bad is they have a tremendous amount of data. what we've been doing is reimagining the good and bad is they have a tremendous amount of data I mean, you're talking about nearly 50,000, somewhere on average between 30,000 and 50,000 unique recruiters every month use their software to manage and place job ads at over 7,000 boards. i mean you're talking about nearly 50,000 somewhere on average between 30,000 and 50,000 unique recruiters every month use their software to manage and place job ads at over 7,000 boards Their data is incredible. their data is incredible It's also been very consistent. it's also been very consistent If you're trying to think about what an agentic reimagining of their solution is, there's nothing better than starting with that level of data set, right? if you're trying to think about what an agentic reimagining of their solution is there's nothing better than starting with that level of data set right The actions they're taking. What we've been doing is in effect taking, and it will be introduced by a project called Tao and then the new job management, set of modules, that is really bringing an agentic, layer across that that's gonna make those tasks, even though they've been relatively efficient, it's gonna take those tasks that those recruiters have to do on a day in and day out basis almost completely automating it. That coupled with our scale, is really I think gonna be very competitive against anybody in the market. The actions they're taking. the actions they're taking What we've been doing is in effect taking, and it will be introduced by a project called Tao and then the new job management, set of modules, that is really bringing an agentic, layer across that that's gonna make those tasks, even though they've been relatively efficient, it's gonna take those tasks that those recruiters have to do on a day in and day out basis almost completely automating it. what we've been doing is in effect taking and it will be introduced by a project called tao and then the new job management set of modules that is really bringing an agentic layer across that that's gonna make those tasks even though they've been relatively efficient it's gonna take those tasks that those recruiters have to do on a day in and day out basis almost completely automating it That coupled with our scale, is really I think gonna be very competitive against anybody in the market. that coupled with our scale is really i think gonna be very competitive against anybody in the market To prove the point, and kind of the on the go-to-market side is, because of not just what we have been doing, but part of that roadmap is, we've resigned and expanded the type of relationships with some of the largest HCM providers out there, Workday, Oracle, SAP. Our fastest sales growth channel for our hiring business today is Workday referrals. We actually are, quote, unquote or whatever you call it, a gold standard, whatever, the gold level partner with Workday, which means they are selling our solutions, and we have a direct integration with Workday. I think that's, it's kind of the combination of us improving the product, having a AI agentic, you know, first approach and a roadmap, and then leveraging very effectively the largest players in the space who are co-selling with us. To prove the point, and kind of the on the go-to-market side is, because of not just what we have been doing, but part of that roadmap is, we've resigned and expanded the type of relationships with some of the largest HCM providers out there, Workday, Oracle, SAP. to prove the point and kind of the on the go-to-market side is because of not just what we have been doing but part of that roadmap is we've resigned and expanded the type of relationships with some of the largest hcm providers out there workday oracle sap Our fastest sales growth channel for our hiring business today is Workday referrals. our fastest sales growth channel for our hiring business today is workday referrals We actually are, quote, unquote or whatever you call it, a gold standard, whatever, the gold level partner with Workday, which means they are selling our solutions, and we have a direct integration with Workday. we actually are quote unquote or whatever you call it a gold standard whatever the gold level partner with workday which means they are selling our solutions and we have a direct integration with workday I think that's, it's kind of the combination of us improving the product, having a AI agentic, you know, first approach and a roadmap, and then leveraging very effectively the largest players in the space who are co-selling with us. i think that's it's kind of the combination of us improving the product having a ai agentic you know first approach and a roadmap and then leveraging very effectively the largest players in the space who are co-selling with us

Speaker 1: Got it. All right. In terms of the cost cuts implied in today's announcement, it's about $25 million-$30 million on an annualized basis, going forward. Really more starting next year on a full run rate basis. Why is now the right time to make these cuts and refocus the company a bit more? Got it. got it All right. all right In terms of the cost cuts implied in today's announcement, it's about $25 million-$30 million on an annualized basis, going forward. in terms of the cost cuts implied in today's announcement it's about $25 million-$30 million on an annualized basis going forward Really more starting next year on a full run rate basis. really more starting next year on a full run rate basis Why is now the right time to make these cuts and refocus the company a bit more? why is now the right time to make these cuts and refocus the company a bit more

Speaker 2: Veritone today has, I'd say, a certain percentage of our revenues is relatively very stable. It's like our baseline run rate with, I'll say, you know, kind of almost locked in, secure, you know, growth and, and X margin. And I'm not gonna give you that exact breakout. VDR, which is an exciting new lines of business, and even the Fed, they're hard to forecast. VDR, Veritone Data Refinery, unlike our SaaS subscription-based businesses, is all consumption-based. When we do a deal with Meta, there is no subscription monthly or quarterly or annual. It's literally they have a demand, we have to prepare datasets. These the size of these deals are, at the lower end, six figures, some of them, on average, seven figures. Relative to our revenue base, right, it's a huge swing. Veritone today has, I'd say, a certain percentage of our revenues is relatively very stable. veritone today has i'd say a certain percentage of our revenues is relatively very stable It's like our baseline run rate with, I'll say, you know, kind of almost locked in, secure, you know, growth and, and X margin. it's like our baseline run rate with i'll say you know kind of almost locked in secure you know growth and and x margin And I'm not gonna give you that exact breakout. and i'm not gonna give you that exact breakout VDR, which is an exciting new lines of business, and even the Fed, they're hard to forecast. vdr which is an exciting new lines of business and even the fed they're hard to forecast VDR, Veritone Data Refinery, unlike our SaaS subscription-based businesses, is all consumption-based. vdr veritone data refinery unlike our saas subscription-based businesses is all consumption-based When we do a deal with Meta, there is no subscription monthly or quarterly or annual. when we do a deal with meta there is no subscription monthly or quarterly or annual It's literally they have a demand, we have to prepare datasets. it's literally they have a demand we have to prepare datasets These the size of these deals are, at the lower end, six figures, some of them, on average, seven figures. these the size of these deals are at the lower end six figures some of them on average seven figures Relative to our revenue base, right, it's a huge swing. relative to our revenue base right it's a huge swing What we've decided to do, and I'll tell you why it's the right time and why we can do it now, is why are we chasing our losses so much? We have a great operating business. We have killer accounts, right? We have great entry points in public safety. We are going to reduce our baseline operating expense by up to 30% to get us that close to profitability even when revenues are moderate in our baseline business. What I mean by that is, when we do deliver the VDR and I'd say some of the more challenging to time when Air Force and some of these government contracts will ramp, we don't really care. What we've decided to do, and I'll tell you why it's the right time and why we can do it now, is why are we chasing our losses so much? what we've decided to do and i'll tell you why it's the right time and why we can do it now is why are we chasing our losses so much We have a great operating business. we have a great operating business We have killer accounts, right? we have killer accounts right We have great entry points in public safety. we have great entry points in public safety We are going to reduce our baseline operating expense by up to 30% to get us that close to profitability even when revenues are moderate in our baseline business. we are going to reduce our baseline operating expense by up to 30% to get us that close to profitability even when revenues are moderate in our baseline business What I mean by that is, when we do deliver the VDR and I'd say some of the more challenging to time when Air Force and some of these government contracts will ramp, we don't really care. what i mean by that is when we do deliver the vdr and i'd say some of the more challenging to time when air force and some of these government contracts will ramp we don't really care We've corrected our right size of our cost structure. Therefore, we can reap the benefits on the outsized returns when the variable revenue happens. Why we can do it now is, first of all, we've been talking a lot about the technology platform. Pretty much all of our applications now are, I would say, on K8s. It's not to get too technical. We finally have transitioned everything to Kubernetes across the board. We're a lot more efficient in terms of the platform and the application layer. We can be much more efficient on how we're managing the applications and the entire infrastructure. We're finally at a point of maturity where you're gonna see more consolidation in sales and marketing and G&A. We've corrected our right size of our cost structure. we've corrected our right size of our cost structure Therefore, we can reap the benefits on the outsized returns when the variable revenue happens. therefore we can reap the benefits on the outsized returns when the variable revenue happens Why we can do it now is, first of all, we've been talking a lot about the technology platform. why we can do it now is first of all we've been talking a lot about the technology platform Pretty much all of our applications now are, I would say, on K8s. pretty much all of our applications now are i would say on k8s It's not to get too technical. it's not to get too technical We finally have transitioned everything to Kubernetes across the board. we finally have transitioned everything to kubernetes across the board We're a lot more efficient in terms of the platform and the application layer. we're a lot more efficient in terms of the platform and the application layer We can be much more efficient on how we're managing the applications and the entire infrastructure. we can be much more efficient on how we're managing the applications and the entire infrastructure We're finally at a point of maturity where you're gonna see more consolidation in sales and marketing and G&A. we're finally at a point of maturity where you're gonna see more consolidation in sales and marketing and g&a To be clear, we are not doing anything that in any way is gonna impede or impair our ability for growth or in any way impair our ability to drive these new exciting lines of businesses. This is, I would say, almost obligatory based upon what we've been able to do. I'm not gonna say it's way overdue, but I think it's time for us to introduce these things to bring that cost structure down. To be clear, we are not doing anything that in any way is gonna impede or impair our ability for growth or in any way impair our ability to drive these new exciting lines of businesses. to be clear we are not doing anything that in any way is gonna impede or impair our ability for growth or in any way impair our ability to drive these new exciting lines of businesses This is, I would say, almost obligatory based upon what we've been able to do. this is i would say almost obligatory based upon what we've been able to do I'm not gonna say it's way overdue, but I think it's time for us to introduce these things to bring that cost structure down. i'm not gonna say it's way overdue but i think it's time for us to introduce these things to bring that cost structure down

Speaker 1: Awesome. All right. Well, with that, I think we can call it a day. I wanna thank Ryan and Veritone. Awesome. awesome All right. all right Well, with that, I think we can call it a day. well with that i think we can call it a day I wanna thank Ryan and Veritone. i wanna thank ryan and veritone

Speaker 2: Yeah Yeah yeah

Speaker 1: for the time today. for the time today. for the time today

Speaker 2: Thank you. Thank you. thank you

Speaker 1: Thank you. Thank you. thank you

Speaker 2: Appreciate it. Appreciate it. appreciate it