Innodata Inc.

Good afternoon, ladies and gentlemen, and welcome to the InnoData Report third quarter 2025 results conference call. At this time, all lines are in listen-only mode. Following the presentation, we will conduct a question and answer session. If at any time during this call you require immediate assistance, please press zero for the operator. This call is being recorded on November 6th, 2025. I would now like to turn the conference over to Amy Agress. Please go ahead.

Thank you, Michael. Good afternoon, everyone. Thank you for joining us today. Our speakers today are Jack Abelhoff, CEO of InnoData, Rahul Singhal, President and Chief Revenue Officer, and Maryse Espinelli, Interim CFO. Also on the call today is Anish Pazekar, Senior Vice President, Finance and Corporate Development. We'll hear from Jack first, who will provide perspective about business followed by remarks from Rahul, and then Maryse will provide a review of our results for the third quarter. We'll then take questions from analysts. Before we get started, I'd like to remind everyone that during this call, we will be making forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, assumptions, and estimates, and are subject to risks and uncertainties. Actual results could differ materially from those contemplated by these forward-looking statements. Factors that could cause these results to differ materially are set forth in today's earnings press release in the risk factor section of our Form 10-K, Form 10-Q, and other reports and filings with the Securities and Exchange Commission. We undertake no obligation to update forward-looking information. In addition, during this call, we may discuss certain non-GAAP financial measures. In our earnings release filed with the SEC today, as well as in our other SEC filings, which are posted on our website, you will find additional disclosures regarding these non-GAAP financial measures, including reconciliation of these measures with comparable GAAP measures. Thank you. I will now turn the call over to Jeff.

Thank you, Amy, and good afternoon, everyone. Our third quarter was another record quarter for InnoData. We delivered record revenue of $62.6 million, representing a 20% year-over-year organic growth and a 7% sequential quarterly growth. Adjusted EBITDA was $16.2 million, or 26% of revenue, up 23% sequentially, showing margin expansion. even after factoring in growth investments I'll be talking about later in this call. Cash rose to $73.9 million, up by $27 million since year end, and $14.1 million since last quarter. Our results exceeded analysts' expectation across key metrics. As a result of strong business momentum, we reiterate prior guidance of 45% or more year-over-year growth in 2025, and we anticipate potentially transformative growth in 2026. This afternoon, I'll share the basis of our confidence, including the significant growth we are anticipating from existing strategic vectors and the strong early returns from new investment areas. I'll then share how we are preparing the organization to reach the next level. I'll start with our existing strategic vectors. Since we last reported, We have continued to make substantial progress, deepening relationships of trust with high dollar value big tech customers. Our deal momentum continues to accelerate with meaningful expansion across a diverse set of foundation model builders, both existing and new customers. Of the eight big tech customers we talked about recently on these calls, we are currently forecasting six of them to grow next year, several, quite substantially. For example, we just received verbal confirmation for additional expansions with our largest customer and verbal confirmations of a deal we expect to potentially result in $6.5 million of revenue with another big tech. Beyond that, our expectations are grounded in the assessment of these customers' 2026 training data and evaluations budgets and the accelerating trust we believe we're earning with them through proofs of concept, pilot, and scale deployments. Now, in addition to these eight customers, we landed in Q3 or expect to finalize shortly five additional big techs. We believe all five of these new big techs are poised to contribute meaningfully to our 2026 growth. Three of these new five, we believe, are positioned to allocate up to hundreds of millions of dollars annually to generative AI data and evaluation. and we believe we're well positioned to capture a share of that spend. It is worth noting that two of these are global leaders in commerce, cloud, and AI. Now let's turn to our new 2025 initiatives, six in total, several of which I'm sharing with you for the first time today, all of which are already bearing significant fruit, and all of which we believe will contribute significantly to 2026 growth. The first initiative has been creating pre-training data at scale. Now, pre-training data teaches the model language, skills, and knowledge. Up until now, our business has been primarily focused on post-training data, which teaches models how to reason, follow instructions, and perform tasks. But earlier this year, we observed researchers drawing increasingly strong correlations between LLM benchmark performance and the quality of pre-training data. Models that trained on higher quality pre-training Kepora consistently did a better job understanding nuance, context, and intent across languages and domains. And when we saw this research, we concluded that our customers would increasingly be seeking sources for higher quality pre-training data. So we invested about $1.3 million to build new capabilities to create high quality pre-training corpora. This has proven to be a great investment. We've since signed contracts we believe could result in approximately $42 million of revenue. And we expect to soon sign contracts which we believe could result in approximately $26 million of additional revenue on top of that. So that's $68 million of potential revenue from these programs that are either signed or likely to be signed soon. These programs span five customers. There are only a few months in motion and are just ramping up. We believe the majority of the anticipated revenue would flow through 2026, but we've already fully recaptured our investment. As pre-training data gains recognition as a strategic differentiator for next generation LLMs, we believe we are well positioned to capitalize on this early trend. Today we announce the launch of InnoData Federal, a dedicated government-focused business unit designed to deliver mission-critical AI solutions to U.S. defense, intelligence, and civilian agencies. We expect this business unit to be a material revenue generator for us in 2026 and beyond. Today we're also announcing that the business unit has won an initial project with a new high-profile customer. We anticipate this initial project to result in approximately $25 million of revenue, mostly in 2026. We have additional projects under discussion with this customer, and we expect them to be large. This new relationship is strategically significant not only for its potential size, but also for the visibility and market leadership we believe it will convey. We expect to issue a joint press release about the relationship prior to year end. We view it as a potential game changer for our next phase of growth. Additional early market validation includes the company's first direct government award from a major defense agency. potential engagements with other prominent defense technology companies, and submitted proposals spanning the DOD, intelligence community, and civilian agencies. What sets InnoData Federal apart is our ability to deliver the complete AI lifecycle, not just data annotation or point solutions, but true end-to-end capabilities from data collection through model deployment and operational support. Our platforms and expertise already serve the world's leading technology companies and Fortune 1000 enterprises. We are now bringing that same proven excellence to federal missions with the security, compliance, and speed the government operations demand. We believe the timing could not be better. Federal agencies are moving decisively to adopt AI. In July, the administration released America's AI Action Plan, and signed three executive orders to streamline procurement and accelerate deployment. The General Services Administration, or GSA, is now revamping its acquisition processes to make AI services easier for agencies to procure. Historically, federal procurement has been slow and complex, but that's changing rapidly, and we intend to meet that demand and that opportunity head on. As we announced today, General Retired Richard D. Clark, a retired four-star Army general and former commander of U.S. Special Operations Command, has joined the InnoData Board. We're excited about his expertise and relationships in helping guide the trajectory of InnoData Federal. Another key focus this year has been on advancing our participation in the emerging sovereign AI market. Initiatives by governments around the world aimed at independently developing, deploying, and governing AI systems as a matter of national interest. These efforts seek to ensure national control across the entire AI technology stack, from the semiconductors on which models are trained to the data that gives them intelligence. We believe this is one of the most significant structural shifts in the global technology landscape. The drive for sovereign capability has already triggered large-scale state-directed investment programs, effectively creating government-backed demand guarantees for the entire AI ecosystem, from chip makers and cloud platforms to data engineering providers like us. As we have toured several countries in the far Middle East, we've been struck by the level of interest in our services. These countries in most cases do not have a homegrown enterprise like InnoData with a proven track record of helping enable generative AI and LLM initiatives. We were rapidly engaging in advanced discussions with sovereign AI entities across several regions, and we expect to announce one or more strategic partnerships over the next few months. Their economic capabilities and desire to move quickly is truly impressive, and we could not be more excited about this newer area of growth for the company. Meanwhile, our enterprise AI practice is also gaining traction and holds promise for 2026. It provides full stack support to help enterprises integrate generative AI into products and operations. For example, the practice is helping a major social media platform automate its content monitoring and monetization workflows using generative AI and assisting a hyperscaler to integrate generative AI into their data center operations for real-time analytics. We expect these projects to typically start in the $1 to $2 million range and offer strong expansion potential and repeatability. We are also in discussions about strategic relationships that could help propel our enterprise AI practice forward in 2026. The next initiative I'll talk about is agentic AI. As I've said before on these calls, we believe agentic AI will unlock the usefulness of generative AI in the enterprise, and their autonomous agents will soon be as ubiquitous as human employees performing many of their tasks. It's still very early days for agentic AI. We're working with big tech model builders to evaluate and refine autonomous agents across many real-world use cases, creating evaluation models and human-in-the-loop systems designed to measure, interpret, and guide agent behavior. We start by judging tasks' success. Did the agent achieve the goal? And then we analyze why the agent behaved the way it did and profile how it generally behaves to inform further fine-tuning. These capabilities, diagnostic judge, task success judge, and profiling judge, are increasingly used in RLHF and RLHA frameworks for agentic systems where agents act autonomously across multi-step real-world workflows. We've also been building agents within our agility platform as a way of enhancing the product and consulting with a number of enterprise customers about incorporating agents within their environments. This brings me to our sixth area of 2025 investment, model safety. As agents gain autonomy, companies must learn how to monitor and continuously improve them. Our goal is to become a trusted partner to software companies and other enterprises, helping them benchmark for safety, reliability, and ethical behavior. Here's one example of the work we are now doing. Recently, we began engaging with a leading chip company to stress test its multimodal AI products. simulating real-world risks like data exfiltration, privilege escalation, instruction manipulation, and multimodal injection attacks. And once we identify vulnerabilities, we generate targeted mitigation data, fine-tune the model, and prove the results with repeatable benchmarks. Our objective is to increase model safety with no degradation in model capabilities from the retraining. We believe the area of model safety holds enormous potential, so much so that we've engaged one of the world's top consultancies to help us refine our product and go-to-market strategy around model safety. That's a quick recap of the six investment areas that we've driven in 2025, several of which we're announcing publicly for the first time today. In every case, our investments have been modest, but our returns have been outsized, and product market fit has come quickly. We believe that there are startups that have raised tens of millions at ambitious valuations to chase some of these same opportunities. Yet we're getting more done, faster, and with far less capital investment at risk. This year, we anticipate incurring approximately $9.5 million of capability-building investments in these and other similar initiatives. This includes $8.2 million of SG&A and direct operating costs and 1.3 million of CapEx. We were also absorbing costs for substantial excess capacity within the organization in anticipation of likely soon to be captured business. While we could have elected not to incur these costs and instead present higher adjusted EBITDA, we believe these investments represent compelling short-cycle investments that position us for accelerated growth in markets. We believe we're prepared to serve and we believe will yield considerable benefits in 2026 and beyond. We've also strengthened our leadership bench and operational foundation for the scale we're anticipating. I'm pleased to announce the appointment of Rahul Singhal as President and Chief Revenue Officer. Rahul joined InnoData in 2019 and has been instrumental in helping shape our strategy and building deep relationships with our largest customers. We're also welcoming two outstanding new board members, Don Callahan, who brings deep digital transformation expertise from Citigroup and Time, and close relationships with Silicon Valley and enterprise CEOs through Bridge Growth Partners, and General Retired Rich Clark, a retired four-star army general and former commander of US Special Operations Command, who brings outstanding defense insight and strong federal relationships Their expertise aligns with our focus on big tech, defense, and enterprise markets. And I'm confident they'll help guide us through our next stage of transformative growth. Finally, I want to thank Nick for five years of board service. Nick has been tremendously helpful to me and to the company. He is stepping away to devote his time to a new opportunity outside of our markets, and we wish him very well. With that, I'll turn the call over to Rahul.

Thank you, Jack. I'm honored to step into this expanded role. Many of you may have seen Time Magazine recently ranked InnoData number 24 on the inaugural list of America's top 500 growth leaders for 2026, recognizing companies that, quote, capture trends and stay ahead of time. That mindset, seeing what's next and acting fast is core to who we are now. You're seeing the result of that today. We are deepening relationships with both existing and new Silicon Valley customers while delivering quick successes across the six investment areas Jack just outlined. An increasing number of world's largest technology companies and enterprises are seeing the value we bring today. Looking past 2026, over the medium and long term, we believe the work we do with frontier model builders will expand and will become more complex. The next generation of models won't just need more data. They'll need more smarter data. Data from simulation labs, large-scale synthetic generation, and RL gems that capture human judgment, context, and values. On top of this, the AI enterprise services market, which we are now successfully aligning to, will likely grow to be 10 or more times larger than the model builder market. We believe InnoData is purpose-built for this broad enterprise transition. Our work alongside frontier model builders give unique insights into how large models are trained, tuned, scaled, and evaluated. And we are succeeding at packaging these insights into solutions that bring value to enterprises. For example, We have just recently begun providing model safety and remediation solutions that leverage the workings we have done hand in glove over the past year or so with engineering teams from leading AI hyperscalers. Today, we are bringing those capabilities to one of the world's leading fast software companies and one of world's leading generative AI chip designers. In short, I believe we are at the very beginning of the generational technology shift that InnoData is at the center of and poised to capitalize on. When I look at the competitive landscape, they're not even a handful of companies that have the capability to service 50 million, 100 million or larger order sizes in our space. And that's the need for hyperscalers today and sovereign entities. Plus, they don't have the proven ability to scale the organization. provide flawless data accuracy, and be highly nimble to addressing the changing client needs in a very dynamic environment. What an amazing time to be alive when the world is going through a seismic change driven by AI, and to be in such a privileged position to help lead a company that is a critical part of catalyzing the change. I'll now turn the call over to Maryse, and after her remarks, we'll be available to take your questions.

Thank you, Rahul and Jack, and good afternoon everyone. Revenue for Q3 2025 reached 62.6 million, up 20% year over year. Sequentially, revenue increased 7% from Q2's 58.4 million. Profit for Q3 2025 was 27.7 million, an increase of 4.8 million, or 21% year over year. with an adjusted gross margin of 44%. Adjusted EBITDA was $16.2 million, or 26% of revenue, up 23% quarter over quarter, deflecting the strong operating leverage in our business. Net income for Q3 2025 was $8.3 million compared to $17.4 million a year ago. The decrease was mainly due to the tax benefit arising from the utilization of net operating loss carry forward in Q3 2024. We ended the quarter with $73.9 million in cash, up from $60 million at the end of the prior quarter and $46.9 million at year-end 2024, and did not draw down on our $30 million Wells Fargo credit facility. As Jack mentioned, based on our current momentum, we reiterate our prior guidance of 45% or more year-over-year growth in 2025, and we anticipate potentially transformative growth in 2026. Thank you, everyone, for joining us today. Operator or Michael, please open the line for questions.

Thank you very much. It is now time for our Q&A. Our first question comes from Alan Klee with Maxim Group. You may now begin.

Great job on the quarter. I was adding up, you mentioned a bunch of potential contract wins and what they could represent. And the ones that you put dollars amount on added up to close to 100 million. But what I wasn't sure about is, some of these could be contracts over multiple years. Is there a sense of what amount of that could potentially be in 2026? Hi, Alan.

So, great question. I think the contracts that we, you know, when we talk about, you know, annualized recurring revenue. Those are generally the contracts that we think will kind of roll at the number that we state is a year's value from that. Other contracts that we talk about, you know, we're going to try to do some ramping up of some of them in this quarter, but then that revenue would primarily be falling into next quarter, excuse me, next year.

OK, thank you. And then In terms of, you mentioned that you're going to spend an extra, I think you said 8.2 million in incremental SG&A. Could you just explain what, that's over what time period? And the way to think of that is over what type of base?

So that would be year over year. And that would be incremental in 2025 versus 2024.

Got it. And then with your largest customer, I think you've mentioned now more than once of the potential to expand the relationship, which could be very large. But any commentary on just the existing business of them? Is that, should that be considered kind of stable?

So the relationship is strong and the business is stable. I think as you'll see, you know, the business went up sequentially in the quarters. And as we discussed just a few minutes ago, we got a verbal on what's potentially a very large new program that would would would come into, you know, with that customer. We haven't really baked that into anything yet because we're not sure what the ramp up would be, but it's certainly very significant relative to next year.

Okay, great. Thank you so much.

Thank you very much. Our next question comes from George Sutton with Craig Hallam. You may now begin.

Thank you quite an update and congrats both jack and role for your expanded roles relative to the verbal comment jack. For with your largest customer I assume that would just run through a an existing statement of work, so you could take that business on relatively quickly.

That's correct. I mean, mechanically, it would run through the existing master services agreement and probably be a new statement of work. But your point is correct that it will be very easy and seamless in order to onboard that new requirement.

So I was thrilled to hear about your federal market win and it begs the question, and I think you addressed it with your GSA comment, but typically you need to be part of a FedRAMP program to take on material business like this. Can you just walk through how you're doing this under this GSA process or what's different than a normal FedRAMP process?

Yeah, so I think that the point that we were making is that the timing for us starting this practice is ideal. The federal government, you know, has clearly communicated the strategic emphasis that they're putting on AI and AI enablement, you know, both in the DOD, you know, the IC, and even, you know, civilian agencies. So you have that. On top of that, They're recognizing that the you know the procurement and acquisition programs and processes are cumbersome and they. Will impede the AI progress that they're intending to make. And therefore they've issued executive orders. I think there may even be some new pronouncements expected to come out tomorrow on that subject. So when you take these two things in combination, the prioritization that the government is placing on AI, again, spanning the entirety of, you know, federal on the one end, and then on the, you know, liberalizations that they're making in terms of acquisition and procurement, it really couldn't be a better time for us to be in that market.

Gotcha. And then finally, Rahul, you made a very interesting comment that the services market could be 10 times the model builder market. I wondered if you could just put a little bit more meat on that. How much of that do you think you've started to see thus far?

Yeah, George. So if you think about the enterprise market today and the frontier models, these models are now getting integrated into workflows that are transforming either for cost reduction, predominantly today for cost reduction, and soon we're going to see transformative workflows that will drive new business models and revenue generating. As we talked about, we are seeing for one large social media company, we were able to dramatically save them over $24 million worth of cost. So it's early stages. We are starting to get into the stage where we are starting to deploy GenAI solutions into our customer base, and we hope to expand this service in the future.

Super. Great job, guys. Thank you.

Thank you.

Thank you very much. That appears to be our last question. I will now turn the conference over to Jack Abouhaf for any additional remarks.

Thank you. Yeah, I guess InnoData is executing really from a position of strength. We had another record-breaking quarter. Revenue is at an all-time high. We see profitability growing, and the results exceeded our analysts' expectations. Looking out ahead to 2026, we see the potential for continued transformative growth, powered by deepening relationships among the MAG7 and other Silicon Valley leaders. And we see that growth coming from two sources. First, the continued expansion we're driving with existing new customers. And then secondly, the strong returns we're beginning to see from our recent investments. Today, I talked about six specific investment areas. And across each of them, across the board, we're showing what happens when we do exactly what Time Magazine recognizes for, seeing what's next and acting fast. So to recap quickly some of these early wins. First, $68 million in new pre-training data wins, $42 million that's signed, $26 million that we believe gets signed very soon. A $25 million win with a new strategic federal customer that we expect to name soon, and we believe this is potentially the first of many projects with them. An additional expansion with our largest customer based on verbal confirmation. 6.5 million verbal confirmation of a deal win with another big tech customer, and new partnerships emerging with key AI and sovereign AI players, which we expect to be announcing in 2026. So thank you all for joining us today. We couldn't be more excited about what lies ahead. Thank you.

Ladies and gentlemen, this concludes today's conference call. Thank you for your participation. You may now disconnect.