Before we begin, I'd like to note that certain statements we may make today, December 1, 2025, could be considered forward-looking. These statements are based on our current expectations and assumptions, and actual results may differ materially due to risks and uncertainties. We do not undertake any obligation to update these statements after today's discussion. For a full list of risk factors, please review the disclaimer on this slide and our most recent filings available at sec.gov. A replay of this webcast will be available later this week via a link on the Investor Relations section of Veritone's website at www.veritone.com. After today's prepared program, we will open the floor for a live Q&A with our presenters. You're welcome to submit questions at any time during the presentations using the chat box. We will review the submissions and address a selection of questions towards the end of the session. Welcome, everyone, and thank you for joining Veritone's AI and Data Economy Forum. We have a full agenda for you today where you'll learn more about Veritone's vision and strategic framing of this exciting market opportunity. We're also going to go through in detail our technologies, products, and solutions, including demos. Finally, we're going to go through our go-to-market and business strategy to continue to drive high growth. In addition to myself, you will also hear from other Veritone leaders, including Sean King and Chris Doe, as well as a few comments from a few of our esteemed customers. First, let's talk about the title of this forum today, The AI and Data Economy. I specifically did not state just AI, but data as well, and Veritone is very focused on both. Succinctly, data is the lifeblood of AI, and in today's world and economy, data is both a new asset class and is becoming a new form of currency. Veritone is a native AI company from our inception in 2014, but we are also a data company defining the future of data tokenization, utilization, and ultimately monetization. Going back to our founding, our company name, Veritone, means truth in the signal. It embodies our foundational belief that the world's unstructured data contains objective truths that, when properly refined, fuel intelligence, insights, and value. We build the systems and applications that process and activate this data to uncover and operationalize this truth and also its value. This data processing at scale has established Veritone as a key enterprise leader in both the AI and data economies. Enabled by our unmatched expertise in unstructured data and our proprietary AI operating system, aiWARE, Veritone delivers market-leading applications and workflows at scale focused on transforming unstructured data into actual intelligence and tangible value. For more than a decade, Veritone has been cognitively processing or tokenizing video and audio, which is the fastest-growing segment of unstructured data. We've been converting this unstructured data into metadata-rich tokens, aligned with faces, objects, speech, sentiment, events, and many more contextual embeddings. Our aiWARE operating system provides a scalable, secure, and AI model-agnostic foundation for the ingestion and operationalizing of both structured and unstructured data across disparate enterprise systems securely, reliably, and at scale. More importantly, we are processing and tokenizing this data in a transactional, utility-driven format that delivers immediate value and measurable ROI for our customers, which includes many of the market leaders from media, entertainment, and sports, including CBS, who you're going to hear from later, to public sector and government, including the United States Air Force and hundreds of state and local law enforcement agencies and sheriff departments. To help educate the audience on what exactly is this unstructured data opportunity and its journey, let me walk you through an example customer, in this case, CBS News. CBS News has been producing millions of hours of unstructured audio and video going back decades. What Veritone does is we work with them as a customer. We ingest all of that raw audio and video into an instance of aiWARE, and then immediately we start applying cognitive AI processing against those audio and video files. This turns it into indexed and organized tokens. Those tokens, think of them as understanding of what's inside every single frame of video and every second of audio, is actually the input that drives these powerful applications. It creates the utility value. At sometimes, it's as simple as search and discovery, helping archivists or researchers find specific points in time or specific elements of content. It helps their sponsorship and advertising groups optimize product placement and also helps drive research decisions, what programming's working, what's not working. The point here is we are the full end-to-end stack from ingestion to AI cognitive processing and tokenization to actually providing the utility value of this indexing through our applications. Today, Veritone stands on a trajectory of strong and strategic growth powered by, again, our AI operating system, aiWARE, which fuels the global data economy by generating trillions of tokens per quarter across all of our customers. As the AI economy accelerates, the data economy is expanding right along with it, and Veritone's strategic positioning and market timing could not be more perfect. Building on our scaled data processing and tokenization of unstructured data with the example that I just gave about CBS News, we are also emerging into an exciting new field, working with hyperscalers and AI model developers to actually help train and tune their next-generation models. In fact, we're using the same audio and video files that we've prepared and cleaned and indexed, and we are now working and licensing and selling that data directly to the largest hyperscalers and AI model developing companies. We call this new solution the Veritone Data Refinery, or VDR. Through VDR, we have established ourselves as a premier data and model training partner for many of the largest hyperscalers and foundational model developers. We transform, again, raw, unstructured audio and video into high-quality tokenized data sets that can be used to train and fine-tune the world's most advanced AI models. VDR is a new product line that is being sold into both public sector and commercial enterprise customers. With a qualified near-term pipeline and bookings already surpassing $40 million, VDR is emerging as a critical partner to many global hyperscalers and the next generation of AI model developers. As we've stated on previous calls, we are confident by the end of the year we will hold active contracts or projects with nearly every major hyperscaler in the market, further solidifying VDR's position as a critical enabler in the unstructured AI training data ecosystem. Our tokenization platform not only powers our AI workflows and customer applications today, but now serves as the foundation for a powerful new monetization framework. The data-as-a-currency era has arrived, and Veritone is uniquely positioned to capitalize. Once data is tokenized through aiWARE, the opportunities are endless for our customers. We're able to help them increase profitability and work more efficiently with data that is instantly searchable, analyzable, and actionable. As content and data libraries expand and data volumes surge, Veritone is uniquely positioned to unlock value from commercial enterprises and IP owners. Our technology enables enterprises, many of whom have been loyal customers of ours for over 10 years, to now fully monetize their content and data archives, transforming dormant assets into active, revenue-generating resources while simultaneously producing high-quality, model-ready training data that fuels the next generation of AI innovation. Now, enough of me talking. Let's pass it over to Chris Doe and Sean King, who are going to actually walk you through our products and services and our go-to-market strategy. Hello, everyone. I am Chris Doe, Head of Product at Veritone, and today I'm very excited to walk through our technology platform, our product portfolio, and a preview of what is coming next year. Before we begin, a quick introduction about myself. I've spent the last 20 years in product management across data, media, and online advertising. I've always gravitated towards the bleeding edge of technology, and that is ultimately what brought me to Veritone five years ago. Today, I oversee our commercial and public sector applications, as well as aiWARE, the platform that underpins all of our AI software and data services. These products are business-critical for some of the largest media companies, sports leagues, and law enforcement agencies in the world. First, I want to ground us all in the technology platform that makes everything you'll hear about today possible. aiWARE is the core end-to-end platform that powers all of our commercial and public sector applications. It brings in large volumes of audio, video, images, and documents, applies AI processing at scale, and converts that raw data into data tokens that can be searched, analyzed, transformed, and monetized. The platform excels at four key areas: ingestion, AI cognition and orchestration, tokenization, and activation. First is ingestion. aiWARE is built to handle data at scale, whether that is a movie studio archive, a live broadcast feed, a series of CCTV networks, or drone footage. All of it can be brought into a single, secure environment with full data provenance, so customers always know exactly where every asset originated from and how it has been processed. The platform also features advanced metadata support and synthetic metadata enrichment options. Second is AI cognition and orchestration. The platform manages a large and growing ecosystem of models, including our own proprietary models and those from the best-in-class providers. All processing runs in a secure, controlled, and explainable manner to support the requirements of both commercial and government customers. As part of this, we developed our own token standard called AION, which provides a consistent way to represent token outputs across all these models. This ensures that every piece of intelligence generated by aiWARE is structured, traceable, and interoperable. Third is semantic tokenization. aiWARE normalizes the intelligence it produces, creating transcripts, labels, timestamps, entities, embeddings, and other forms of structured metadata. This is what enables clean and consistent search across all of our products, including natural language search, which you'll see throughout the demos today. Finally, activation. The intelligence generated by aiWARE can be activated in multiple ways. In most cases, the activation is within our purpose-built applications, but in other cases, the value is achieved in dashboards, alerts, data exports, and third-party integrations. Activation is where business outcomes are achieved. As we move throughout the demos, remember that all the applications you see today are not point solutions. They're built on one platform and one single architecture, aiWARE. Having introduced aiWARE and how our underlying platform ingests and cognitively processes the unstructured data, we are now going to dive into our application layer, which ultimately turns this value into our customers. Starting in commercial, the initial application I want to discuss is Digital Media Hub, or DMH. DMH is our intelligent media asset management, archive, and monetization solution for all of your creative content. DMH is used by many leading sports, news, and entertainment clients worldwide, including CBS, NBCUniversal, Augusta National, and ESPN. DMH got a major upgrade this year and is faster, smarter, and more integrated than ever. We have enhanced our AI-powered tagging, streamlined the user interface, and introduced powerful new collaboration tools. The real magic is the AI. Automated tagging and processing allows the user to instantly begin searching across the indexed data. Users can simply enter a term, phrase, keyword, and automatically be taken into the exact moment they are looking for. No more manual tagging. Users can also leverage our advanced moment search built on top of a vector database that allows for a more semantic-type search experience. DMH also now includes upgraded commerce tools that simplify rights management, pricing, and transaction processing, making it easier to monetize your archive. With automated workflows and cloud transcoding, delivering assets to the right destinations is faster and more seamless than ever. We have also introduced new customer-driven features, including bulk tools for metadata updates, ordering, and organization, as well as a redesigned collections experience that makes sharing and collaboration easier than ever. As you can see, DMH delivers a deep set of capabilities that support an impressive range of customer needs. Next, let us look at our long-standing Discovery product, which is used to ingest and analyze thousands of television, OTT, radio, and audio streams 24/7. Here, you can see how users can search radio and broadcast television streams using natural language. This enables media broadcasters to derive programming insights in a matter of seconds. Discovery also includes one-click tools that generate concise data summaries and actionable campaign recommendations. Most recently, Discovery has been fully integrated with our chatbot, Very, giving users interactive search and deeper content intelligent insights. Very is the result of more than a year of innovation from our labs team. It's an amazing tool to summarize all the AI processing results that are attached to the ingested files. Users can ask Very to summarize large watch lists, break down key moments, and answer follow-up questions in real time. They can refine their results by adjusting confidence levels, request deeper context, or even ask for the sentiment of an entire video. Very delivers these insights in seconds, turning complex analysis into a simple conversational experience. Now, let us shift into our public sector applications. This is one of the fastest-growing areas of our business, and for good reason. Digital media analysis has become essential for modern policing and investigative work. In many ways, it is becoming the new DNA analysis. Agencies are dealing with enormous volumes of video, audio, documents, and digital evidence, and there's just simply no way they can process all that information manually at the scale required. With that said, let's talk about Veritone's intelligent digital evidence management system, also known as Veritone iDEMS, our solution that helps public safety and justice agencies accelerate their investigations. Veritone iDEMS is a suite of AI-powered software products, which I'm excited to show you now. The first application in iDEMS is Investigate. This product helps investigators quickly find key moments across large sets of evidence, connect related items, and collaborate more effectively across cases. It brings every file into one place, along with all the associated metadata and AI-generated insights so that everything is searchable and easy to navigate. Investigate also connects seamlessly with all the rest of the iDEMS products, ensuring that all the evidence and workflows stay linked across the entire investigative process. Next is Veritone Track. Track uses advanced computer vision to help investigators locate a person of interest across large collections of video. This goes far beyond simple face recognition. Track evaluates appearance, clothing, movement patterns, and other visual attributes to find matches across different cameras, angles, and environments. As you watch the demonstration, imagine an investigator needing to search across dozens of CCTV feeds to identify where a person may have been. Traditionally, this could have taken days or weeks. With Track, that work can happen in minutes. The system presents potential matches, timelines, and movement paths so investigators can quickly understand where a person may have traveled and which footage is most relevant. It accelerates investigations while reducing manual review time in a significant way. The end result of this workflow is a shareable person-of-interest timeline to help solve active cases faster. Now, back in the Investigate application, I can search for a transcription keyword and show you how Redact works. Redact is one of the most widely used public sector applications and solves a very real-world challenge. Agencies are required by law to protect PII, personally identifiable information, when releasing body-worn camera footage, dash camera footage, or other evidence. Historically, this meant someone had to go frame by frame and manually blur sensitive information. Redact removes that burden. As the video plays, you can see how Redact automatically detects sensitive keywords and applies accurate, frame-consistent masking. The same workflow is possible for faces, screens, license plate, and coming soon documents. In the next example, after running another simple keyword search and navigating to our data detail page, you will see the automatic video summarization applied to the body camera footage. This is a straightforward but powerful demonstration of how we save investigators significant time while showcasing the strength of our video understanding capabilities. We will be adding additional police report generation capabilities next year and also adding Very so detectives can talk to their evidence if they so choose. Together, these capabilities highlight how iDEMS delivers the workflows and intelligence required to drive better investigations. In the end, it's all about catching the bad guys as fast as possible. One of our most exciting advancements in our product portfolio over the last year is the Veritone Data Refinery, or VDR. Introduced late last year, VDR represents the next evolution of our aiWARE platform, taking everything we've built in multimodal ingestion, cognitive AI processing, and semantic tokenization and elevating it to a new strategic tier. For years, aiWARE has powered our applications by transforming raw video and audio into structured, machine-readable intelligence for our customers. With VDR, we've extended that same architecture to a new frontier, preparing and refining tokenized video and audio as high-quality training data for modern AI models. This offering isn't theory. It is a direct application of our core expertise. aiWARE's proven ability to ingest, structure, and cognitively analyze the unstructured media now allows us to produce training-ready data assets at scale with the consistency, transparency, and operational rigor that model developers require. VDR is both a product and a service engine, a full-stack pipeline that transforms enterprise archives into AI-ready intelligence, unlocking new revenue streams for rights holders and accelerating model development for AI companies. It is one of the clearest expressions yet of how Veritone's technical foundation, proprietary workflows, and domain experience position us at the center of the data economy emerging around next-generation AI. What are we working on for VDR for next year? We are going to be introducing a lot more advanced token generation services via advanced clipping and annotation tooling. Our goal is simply to provide the best quality training data to our partners and overservice them throughout all engagements. Looking ahead, we are entering one of the most transformative periods at Veritone. Several years of deep platform and application investment are coming together, and we are about to enter a new era of innovation at Veritone. A major theme will continue to be natural language. Users across all of our products will be able to leverage our chatbot, Very, to talk to their data for search, analysis, workflow execution, like we showed earlier in Discovery. To be clear, we will always support the structured user experience our products offer today, but we will complement those experiences with a natural language alternative if clients so choose. You will also see more advancements in video understanding. As more models are introduced into the market, you can ensure Veritone will be testing, onboarding, and benchmarking all of those for our clients. Next, real-time video analytics is something I'm very excited about. Veritone has a long track record of delivering real-time AI insights that help our customers make business-critical decisions. Doing that reliably at scale is incredibly difficult. This is what we excel at, and we have both the experience and the vision to continue leading in this area. Finally, Agentic workflow. Today, the super majority of our utility value realized by our end customers is through the application layer. Yes, these AI-enabled applications, including DMH, Redact, Investigate, and others, have greatly improved the speed and efficiency, but the ultimate yield potential of all this centralized tokenized data is still constrained. This is where Veritone Agentic AI will exponentially increase performance and yield. Imagine the same homicide detectives using Investigate can invoke a swarm of Veritone AI agents to not only enable them to analyze multiple crime scenes at the same time, but these agents can immediately start taking action on potential evidence, hits, and elements of interest to advance or follow up on. Now imagine a police department using the same technology to monitor dozens of city cameras, receive real-time alerts for person of interest, and immediately pull relevant case evidence through natural language search. Investigators collaborate on the same data in minutes instead of days. On the commercial side, imagine a major television network running hundreds of live feeds and simply asking Very to track brand exposure in real time, or identify story moments, generate highlight clips, or flag compliance issues. All automated, all instant. These examples are why we are hard at work adding Very to all of our applications, many of which are scheduled to launch in this upcoming quarter, Q1 of 2026. In sum, next year's roadmap is the most exciting we've had in my five-year tenure. I'm incredibly optimistic about 2026 and the evolution of both our product portfolio and our service offerings, all powered by our comprehensive aiWARE platform. You may wonder why I'm so optimistic. Well, look at 2025. Veritone created a rocket ship business line called VDR pretty much out of thin air, and this was because they used the aiWARE platform. A platform that allows builders to launch new products and solutions quickly and efficiently in a secure and compliant fashion. I can't predict the future, but I do know we have a lot of entrepreneurs on staff, and I guarantee there will be more lines of business sprouting up in years to come. That's why I'm so optimistic and so why I'm so bullish about aiWARE. Thank you for spending the time with me today. I want to thank all of our customers, partners, and employees that made this possible today. Hi, I'm Sean King, Chief Revenue Officer here at Veritone. Our overarching message today is clear. Veritone has built the market-leading tokenization platform, and our decade of revenue growth has resulted in one of the largest and most comprehensive libraries of tokenized audio and video data. These tokenized data assets are what power our applications, as Chris demonstrated, providing operational efficiencies, production gains, and net new revenue opportunities for our customers across both commercial and public industries. This foundation allows us to serve an industry-agnostic customer base around the world. Our aiWARE platform powers organizations across media, government, sports, and enterprise sectors, from global broadcasters and hyperscalers to law enforcement and Fortune 500 companies. Because aiWARE is adaptable to any data type and workflow, we deliver value across diverse industries and use cases, whether data needs to be analyzed, managed, or monetized. Today, you'll hear from a few of our customers demonstrating how we help leading organizations unlock the full value of their data. As our advanced AI and data capabilities have strengthened, we are seeing not only new business wins and renewals, but contract expansions allowing our customers to fully harness their data assets. As Ryan mentioned at the start, the data-as-a-currency era has arrived, and Veritone is helping our customers lead it. Every organization sits on vast, underutilized data, and we help them turn it into living, monetizable assets. Through Veritone Data Refinery, alongside our licensing services, our customers transform video, audio, and text into tokenized, model-ready data sets, as well as commercially ready media assets that unlock new revenue streams, help enrich and improve the creative process, and accelerate AI innovation. Our customers, whether in media, government, or enterprise, gain the ability to control, enrich, and transact on their data safely and at scale. As data becomes the world's newest currency, Veritone enables our customers to fully participate in the emerging data economy and create measurable value from every token. Now let's hear from one of our long-standing customers, CBS News. I'm Maggie Dakin, Director of Archive Sales for CBS News Archives. For over 90 years, CBS News has documented the most pivotal moments both in our nation's history and across the globe. Over time, it became clear that these stories would hold immense value for generations to come. With that, the CBS News Archives was born. We have been partnering with Veritone Licensing for the last decade to make our content available for storytellers, creating moving and informative films, documentaries, episodic series, and podcasts. As we digitize our archives, Veritone's aiWARE provides a unique opportunity to solve one of the biggest hurdles in our business: search and discovery. As we look to our digitizing our entire archive, Veritone's technology will play a pivotal role in improving the licensing experience for creatives. Now let's shift to one of the fastest-growing, most critical areas of our business, public sector. Today, digital media analysis has become essential to modern policing and investigative work. It is, in many ways, the new DNA analysis. Law enforcement and public safety agencies are facing a data challenge of immense scale, dealing with enormous volumes of video, audio, documents, and digital evidence from body cameras, surveillance videos, and other sources that are simply impossible to process manually. Veritone's Intelligent Digital Evidence Management System, or iDEMS, is the direct solution. It's a suite of AI-powered tools designed to not just manage this data, but to accelerate investigations and deliver better outcomes. Our iDEMS suite showcases compelling use cases that directly solve the most painful points for our customers. Veritone Investigate helps the team find the crucial signal in the noise, connecting evidence and enabling collaboration. Veritone Redact addresses the mandatory compliance challenge with releasing public records, replacing weeks of manual frame-by-frame blurring with automated, accurate masking of faces and personally identifiable information, or PII. This is an unmatched win for efficiency, privacy protection, and transparency. Lastly, Veritone Track leverages advanced computer vision, turning days or weeks of manual video review into mere minutes, locating persons of interest across vast video collections. Collectively, iDEMS delivers faster investigations, more successful case outcomes, and strengthens the vital relationships between agencies and the communities they serve. Now let's take a moment to hear from our customer, Eden Prairie Police Department. My name is Alyssa Benkowski. I am the Records and Evidence Supervisor with the Eden Prairie Police Department. The Eden Prairie Police Department maintains a large amount of digital data captured by over 90 body-worn cameras, 30 squad cameras, and several interview room cameras. Each year, our agency responds to over 40,000 calls for service. With only three record specialists, in addition to their day-to-day responsibilities, they respond to approximately 2,500 public data requests each year, so it is imperative that our tools are accurate, efficient, and dependable. My first body-worn camera project was for a 15-minute video, and with our old system, it took me over eight hours to complete that project. When we tried Redact, I ran that same video as a comparison, and I finished that in about an hour. The transcript feature and head detection immediately stood out to me, especially since facial recognition alone does not tend to keep up with people when they are turning their heads or when officers are moving within the frame. Redact's upload speed, transcript processing, object detection, and integration with our evidence management system have made a big difference for us. We no longer waste time downloading and re-uploading files, and multiple staff members can work on those projects at any time, which is essential for the volume that we are dealing with. In addition, we recently learned that muting and beeping audio does not meet our state requirements, which are two of the only options that most systems offer. When I reached out to Veritone after learning this, I received a very prompt response that audio masking had recently been implemented, and they worked quickly to turn that feature on for our department. This leads me to one final thought. One of the main things that stands out about Veritone is their customer service. Their team is quick to respond, always helpful, and makes it known that our needs truly matter. Even if I contact the wrong person, I'm always routed to the correct one right away, and I never feel like I'm inconveniencing anyone over there. They really take a lot of pride in their products. Redaction will always be a big and sometimes daunting task, but with Veritone Redact, it has made it much more manageable. It helps us stay compliant, maintain transparency, and keep our workflow moving. We are truly grateful for the difference that this has made in our processes. It's absolutely incredible to be able to service such customers. It takes a robust go-to-market strategy to drive the kind of revenue result we saw in third quarter. Our customer contracts are generally subscription-based, consumption-based, or a combination of both, enabling flexibility to meet a wide range of customer needs. We serve thousands of existing customers through these models while leveraging both direct sales efforts and a strong partner ecosystem to attract new prospects and build a healthy, sustainable pipeline. Our go-to-market strategy centers around direct sales motion supported by a strong, diversified partner ecosystem. By prioritizing direct opportunities, we can ensure tight alignment with our customer needs, shorter feedback loops, and deepen engagements across the industries we serve. This motion is amplified by our robust partner network that extends our reach and accelerates adoption. Today, we leverage hyperscalers, system integrators, and channel partners like AWS, MissionRT, Technology North, Key Code Media, Carahsoft, OPEXUS, and NUX, just to name a few. We also align with necessary technology alliances like the AWS Generative AI Center of Excellence to meet customer needs where they are. Together, these complementary motions enable Veritone to scale efficiently, understand new and developing needs, and deliver AI and data solutions that are operationally transformative. Ultimately, our message is clear: Veritone is the company that transforms vast, underutilized data into living, usable, monetizable tokens. These tokens power our customer applications and all monetization opportunities. Through aiWARE, a market-leading tokenization platform and its intelligent applications, we are empowering organizations across every sector, from media to law enforcement, accelerating innovation, achieving measurable value from every token, and fully leading the data-as-a-currency era. Thank you all for your time today. Over to you, Ryan. All right. We are going to have a little live Q&A here. Let us kind of assemble our team, make sure I see everybody, and then I'll turn over to Cate, who is helping organize the questions. First, just want to thank you, everybody, for joining today. Obviously, we have a pretty exciting and dynamic team over here. Thank you, Chris. Thank you, Sean, for being representatives of a very large, much larger organization. There are a lot of people who contributed here. Before we kick it off, I want to just impress upon people really the power of our core technology platform that makes all this not just possible, but so cost-effective for us to continue to iterate and build these effective workflows and these solutions for our customers. All right. With that, Cate, can you assemble the questions, and let's get through these? Sure. Thanks, everyone, for submitting questions throughout the session. We also have a few analyst questions that came in before the session today. Ryan, just to get started, this came in from the chat. The White House officially launched the Genesis mission last week. Can you talk about how this will impact the business for Veritone and the public sector opportunity set that we've spoken about? Yeah. I think you're referring to last week, the White House again issued an executive order named the Genesis mission. I hope everybody has a chance to go through that. It's not too long. We'll follow up to all the attendees today and give you a link to that. Candidly, this was an exciting advertisement for Veritone and our core thesis and mission. It really sets out two things. One is we obviously know about everything that OpenAI and NVIDIA and everybody else are doing as part of this huge AI infrastructure build-out. I think finally, Michael Kratsios, the CTO of the White House, and respective team, Gill included, they really set forth, which I find a lot of passion and I think is very important, is what is our nation's core foundational model thesis as well, not just being overly reliant, candidly, on just third-party companies. I think this was a major step forward. Here are the two main points of this executive order that I think are so relevant and powerful to Veritone. First and foremost is, if you read this, this is as much about data provenance and leveraging proprietary data as it is about having our nation build its own proprietary AI foundational models. Please read through that. Probably the most impressive thing for our nation and with this executive order is the President's mandate to activate and leverage the legacy existing research and science foundational data sets that the United States has been producing for decades and decades, which includes petabytes and petabytes of audio and video as well. Again, this for us is a testament to our maniacal focus on all things data and the tokenization of that data to turn it into clean, both semantic utility value, as Chris went over in depth today as well, but also providing future AI model training. I think this is a validation of our business model. Yes, if you're going to ask the question, we hope to be part of this exciting initiative. Obviously, as one of the companies that has been processing petabytes of audio and video for decades now and producing high-yield tokenization, we hope to be a part of this exciting initiative with the government directly in the future. I think this was a phenomenal thing. I'm personally proud of it. I'm proud of it as an order for our nation. I do think it's very relevant and helps validate Veritone's core business model and thesis. Thanks, Ryan. That's a very helpful color. Moving to the next question. I know during today's event, and especially during Veritone's last earnings call, data tokenization was kind of at the forefront of your prepared remarks and some of the industry insights that we've been speaking to. Why is this such a major focus for Veritone? Can you help us kind of contextualize what broader tokenization trends you're seeing across the market and how this impacts our market opportunity? Sean, why don't you start off, and then I'll try to follow up and add to this where it deems fit. Sure. Happy to. As kind of both Ryan and Chris said throughout this, for more than 10 years, Veritone has been turning audio and video data on behalf of our customers into tokens and ultimately becoming one of the top-tier semantic token factories that exist, frankly. Our solutions, as kind of Chris demonstrated, were built to transform that raw audio and video into valuable metadata-rich tokens that are basic building blocks for powering our applications, powering search and discovery of assets, as CBS News kind of demonstrated earlier. This really puts Veritone in a great spot because there's still the growing need for structured data that can actually be utilized and then utilized and monetized. These tokenization processes and trends that you're seeing are a massive opportunity for Veritone and our customers to make the most out of their assets and be able to provide high-quality data. We've talked a lot throughout this as data-as-a-currency era is upon us. I believe I read from Mordor Intelligence that the global tokenization asset is expected to hit somewhere north of $10 trillion by 2030. Veritone, as we sit here today, we're perfectly positioned here to take advantage of this. We do that with our strong track record and subject matter expertise. Really, at the end of it, it's our aiWARE platform that can be the engine for that global data economy, as well as our Veritone Data Refinery, as a key of turning that into a powerful new way to grow organizations and Veritone and our customers. As the data and AI industry continues to take off at lightning speed, as I mentioned, aiWARE alongside VDR and our decades of subject matter expertise places Veritone squarely at the center of this expanding opportunity. Great. Thank you, Sean. Don't need to add anything to that. Thanks, Sean. I think we'd love to hear from you two as well, Chris, Ryan, on this one. When you talk about the versatility and flexibility of the aiWARE platform that powers Veritone's products, are there any limits to the platform and its capabilities? Chris, go ahead. aiWARE is truly an impressive technology. It's what attracted me to Veritone years ago, this vision for an AI operating system before AI was mainstream. First and foremost, it fuels all our applications like we've talked about before, both the purpose-built ones for our BUs as well as all the custom applications, workflows, and dashboards that we've built over the years through our professional service offerings. Secondly, as I've said multiple times and you've heard today, aiWARE shines at high-scale ingestion and processing across all formats and across all environments. We talk a lot about audio and video, but we're also very competent in structured data as well as document understanding. For structured data, we get log files from advertising campaigns or telemetry from drone footage, and we ingest that and map that to our systems. On document understanding, opening up these PDFs and understanding all the structure of the tables, graphs, and text, it's not trivial. And we do that all day long as well. Thirdly, aiWARE is hardened and meets all the security, reporting, and compliance requirements across all of our client engagements. These are very complex operational demands that we have been consistently meeting for years. Lastly, aiWARE is open. What I mean by this is it's deployment and model agnostic. On the deployment front, we host our applications in both Azure and AWS, but we're also deployed in GovCloud as well as FedRAMP for our secure federal clients. On the model front, we have an open model framework. What this means is you have a seamless integration and management across hundreds of pre-trained AI models. This allows clients to pick and choose the model that works best for their business and evolve over time as their business evolves. AI is changing, and businesses are changing, and aiWARE supports this evolution. Given all this, aiWARE can really support endless AI solutions, and it's really architected for innovation. Builders can get up and running quickly, prove out the use case, and start scaling operations from there, all possible from the years of technology investment into aiWARE. It's really an extraordinary platform, and it's only accelerating. I think I'll add just one comment. I think this was kind of an add-on from Josh Reilly at Needham, who was asking about our focus, our ability to continue to develop pre-built applications for specific verticals, like Redact for public safety, like DMH for commercial. First is I hope you got a good insight onto the aiWARE platform. What is so powerful, it allows us, really in a low-code workflow type of environment, to spin up and activate against new market needs or problem sets very quickly. Once we have the data, once we've integrated it, once we've tokenized it, frankly, we can build new custom workflows incredibly fast. Our end users may see a huge difference when they're using the redaction software, but candidly, that's just a different workflow. Frankly, to us, from a technology perspective, there's not much of a difference than an archivist at CBS News using the aiWARE applications to solve their problem sets. I think we're in a great position to continue to build these point-specific or solution-specific applications, frankly, that are easy to sell and that are easy to, frankly, train a new end user to use quickly. We are also adept at helping build custom solutions or custom workflows for much larger and more dynamic customers like the Air Force. Hopefully, that answers your question. Again, it all terminates and begins and ends with the aiWARE platform. Thanks, Ryan. Turning to the chat, I believe this was a question that came up during one of the demos. From the audience, on the DMH product, who would be using this? Is it the owner of the content or others looking to access the content? If you could expand on the utility of this as well as the revenue model. Chris, I'll take this, and then maybe you can add a couple of comments if you want. First, DMH Digital Media Hub is primarily used by our commercial customers, heavy usage by media and entertainment, sports, and news organizations. The question is pretty astute. It is actually used by both internal teams, such as the team at CBS News or at CNBC or others, but it also has permissioning, so third-party customers or those who have credential rights can access specific content objects as well. In the context, let's say of the Masters Golf Tournament, they internally use it for management of their files, the speed of building highlights, the speed of preparing content for sponsor activation. On the opposite side, with those who have permission, they can log in and get access to those files almost immediately. When you see Tiger Woods' footage from the Masters, or more recently, Rory McIlroy from the Masters, show up in an advertisement in just a few hours, that's because Wieden+Kennedy and the advertising agency or other third-party customers have also permission-based access. Again, that permissioning is critical. This goes back to the core fundamental functions of aiWARE, where once the data is ingested, it has object-level permissioning down to very specific, I'll say, elements of audio and video. This is a highly high-use critical component for both internal use cases by a lot of our DMH customers, but also has permission-based support for third-party entities who are gaining access to those files as well. Thank you for the question. Thanks, Steel. This was originally a question that came from Josh Reilly at Needham and seeing a few other questions in the chat just around the hyperscalers and their use of the VDR product. For VDR, it seems initially the largest hyperscalers are proving to be customers of Veritone, but that seems to be expanding into a much wider group now, Ryan, as you mentioned. How big is this customer set for VDR over time? Sean, why don't you take this? Sure. I just want to reiterate, kind of as Ryan said earlier on, we're still on track to secure contracts with the majority of all the hyperscalers by the end of the year, which is great because, let's face it, right now, they're the big spenders in the AI space. I just want to reiterate here, this is still very early days. Today, we may see 30 or so major players in this space, but we expect that number to explode into the hundreds over the next couple of years. New groups will be building fresh applications for unique use cases. Some may be layering on top of existing technologies, fine-tuning models, creating very domain-specific use case models. There's a lot of different opportunities, but what is at the base and foundation for all these opportunities is the need for quality data to get started. That is where Veritone has the opportunity to come in. That is our expansive opportunity. Where we have that chance to be their trusted partner to helping them quickly obtain, annotate, prepare that necessary data, we very quickly have the opportunity to really become mission-critical in their processes. I think I would say if the total ecosystem where the super majority of the VDR customers is 50 companies or less today, I expect that to be an order of magnitude bigger over the next couple of years or even into the thousands. We have that conviction because, candidly, the cost of building models continues to drop. Obviously, with this huge AI infrastructure build-out, the cost of compute, the cost of storage continues to fall. Thus, a lot of these companies, many of which are venture-backed or private equity-backed startups, have now more capital that they could use to actually train the models. Again, we are already seeing new players in the space, and we expect the unique number of customers that we are selling and licensing this clean data to them to increase over the next couple of years. On the heels of that, another question from the audience in the chat around the VDR product offering. Can you please explain how the VDR contracts are structured? Are these consumption-based, subscription-based, or one-time fees? Can you add a little bit more color of how those revenues come in? Today, the majority of the VDR contracts are consumption-based. There are elements that you could deem as subscription-based, and we do see sort of the business models change over time. Remember, in the VDR business, we sit on both sides of the equation, which is exciting and creates an interesting moat for us. On one side, we are often the exclusive, I'll say, representation technology partner of the content provider, so let's say CBS News. On the flip side, we are also the vendor or partner with the buyer, one of the hyperscalers, who is looking to procure and license that proprietary data. As it is today, the majority of these contracts is consumption-based. In certain times, depending on what the needs are, some of these contracts are actually one-time fees. We deliver the fully clean prepared data set, and that's it, and we recognize that revenues in quarter. You will see that model change over time. As we process multiple orders, if you want to call it that way, or multiple data programs for a single existing customer, you're starting to see specialization happen already, which, by the way, is really unique because we can offer specialization, meaning I can deliver video files or audio files with different structured formatted metadata or tokens to different hyperscalers to suit their needs, to make their process more efficient. Thus, you could see more subscription-like revenues in the future. To be very clear, today, the majority of our VDR revenue and the recognition of such is primarily consumption-based and also includes elements of one-time fees. Why don't I just take a couple? I know we're running out of time. Cate, how much more time do we have before we need to wrap up here? Just a couple of minutes? We have just a couple of minutes, around six minutes. Ryan, if you want to. Yeah. There's a few interesting questions. I apologize. I'd love to answer all these. We can try to get to some follow-ups with our IR team and our team to reach out to these people. There are a lot of great questions. One, obviously, says, are we expecting any new hyperscaler contracts to be could be released before end of year? To be clear, we're signing those in quarter, and we have signed new ones in quarter for fourth quarter. I think you're looking for more public disclosure. Candidly, we would love to be able to screen for the mountaintops. I mean, obviously, people can infer the type of companies and which specific companies we are working with and selling to. Obviously, we're going to honor the confidentiality of those agreements. This kind of ties into my answer on the President's executive order. Again, it's not just the models. It's the data. Often, what data these companies are using and how they're using it is, frankly, state secrets. Again, all I can reaffirm what Sean said is we are working with the major players today. Hopefully, we'll be able to mention their names specifically more publicly in the future, but be reassured that we are working with the majority of the players already today, some of the biggest names you know. Again, we expect to have relationships and active engagements with the super majority of all of them by the end of the year. Excuse me, then I'll answer one more question and then we can kind of wrap it up for this session today. Again, it says, "Much of our fundraising has been secured from institutional investors. Do you see prospects for strategic investments in the company in the future?" Absolutely. We've had opportunities to enter into more strategic relationships with different major players over the years. Historically, we've elected not primarily for being independent and, frankly, remaining Switzerland. What I mean by that is, as Chris articulated earlier, our platform is completely agnostic. We have customers right now using AI or applications that are using those, and those are deployed on Azure, on AWS, in FedRAMP, and other providers. We also work with countless AI model developers as well as us producing our own AI models internally. We want to make sure that when we evaluate strategic opportunities, that it does nothing to disrupt our independent open thesis, which has proven to be very successful. Again, we are always opportunistic. We are always looking at what type of strategic relationships would be a force multiplier for the company, which may or may not include a direct investment as well. Thank you for a great question. Thanks, everyone f or all the questions, I am going to put in the link to our IR email alerts in the chat. Would love for you all to subscribe, and that is where we will be sharing further updates, whether it is press releases or product updates, as well as the upcoming conferences Ryan and team will be attending. Really appreciate everyone attending today's session, and we'll turn it back to you, Ryan, just to close this out. Again, thank you, everybody. A few things I want everybody to get from this session and webinar today is, first, just alignment. If you can hear how Chris speaks to our opportunity through the lens of product and engineering, how Sean speaks to it from go-to-market and revenue generation, and obviously how I speak to it from a strategic perspective and market perspective, we are all in on what we've been doing for a decade, our ability to be the experts on leveraging AI and fueling AI with unstructured and structured data, tokenizing it, and bringing almost immediate ROI and utility value to the opportunity and to the marketplace and to our customers. We're very, very excited about that. Please pay attention to this phenomena of the tokenization of real-world assets. That's what we do. Audio and video is a real-world asset, and we are definitively a market leader in that space. We're very bullish about VDR. We're very bullish about what we're doing in public sector and in commercial. Again, I think we have many different levels of moats. People always ask, "What's proprietary? What's different?" To be clear, it's all of it combined. Achieving this level of scale and achieving this number of real customers that are going to, most of which have been customers of ours for years, we have almost like the network effect where we can leverage our same core operating system, aiWARE, to service radically different types of customers in completely different market segments, but all running on the same stack. That's incredibly hard to do. It's incredibly challenging. Veritone has not only been doing that successfully for years, but we are also servicing some of the largest enterprise customers. Look at the names of our customers that have been with us for a long time. I want to thank my team. I especially want to thank representatives from CBS and police departments for joining us today and supporting us. We will try to answer all your questions and follow up via email, but I appreciate your time today. We look forward to closing out a very strong year. Thank you. Thank you.