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Date
Thursday, July 31, 2025 at 9:00 p.m. ET
Call participants
Chief Executive Officer — Jack Abuhoff
Interim Chief Financial Officer — Marissa Espineli
Senior Vice President, Finance and Corporate Development — Aneesh Pendharkar
Senior Vice President, Legal, Corporate Affairs & General Counsel — Amy Agress
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Takeaways
Revenue: $58.4 million in Q2 2025, representing a 79% year-over-year increase compared to Q2 2024.
Adjusted EBITDA: Adjusted EBITDA reached $13.2 million in Q2 2025, growing 375% year-over-year, reflecting increased operating leverage.
Net income: Net income reached $7.2 million in Q2 2025, reversing a net loss of $14,000 in Q2 2024.
Adjusted gross margin: 43%, up from 33% a year earlier.
Cash position: $59.8 million in cash as of Q2 2025, with an additional $8 million payment received shortly after the quarter's close.
Credit facility: $30 million Wells Fargo credit facility remains undrawn, providing liquidity and flexibility.
Full-year revenue guidance: Raised full-year 2025 organic revenue growth guidance to at least 45%, up from the previously communicated 40%.
Largest customer revenue: $33.9 million in revenue generated in Q2 2025, with multiple new projects secured and further opportunities in pipeline.
Key new tech customer: Secured $10 million in expected revenue for the second half of 2025, up from $200,000 in the trailing twelve-month period.
Strategic investment: Approximately $1.4 million in Q2 2025 operating expenses targeted at new hires in delivery, product innovation, go-to-market, and talent acquisition.
Future investments: Management signaled plans to “substantially increase investments” while maintaining a goal of exceeding 2024 adjusted EBITDA results (non-GAAP).
Tax rate guidance: An expected tax rate of approximately 27%-28% for the coming quarters, subject to tax environment stability.
Market opportunity: Management expects agentic AI and simulation data services to become major future growth drivers, potentially surpassing frontier model data markets.
Competitive dynamics: CEO Abuhoff stated, "we believe that their shift in focus is likely to accelerate market opportunity for us."
Summary
Management highlighted a record quarter in Q2 2025, marked by rapid revenue expansion and proactive guidance increases, fueled by new project wins with both existing and new large technology customers. Investment in advanced AI and data science capabilities positionedInnodata(INOD -0.26%) to address structurally growing opportunities within generative and agentic AI, while organic growth remained the focal strategy as reinforced by current performance and future outlook statements from executives.
CEO Abuhoff indicated plans to invest in simulation and evaluation platforms for AI and robotics, which may establish new addressable markets.
Management described growing integration with client data science teams, citing a transition from delivering data to “sitting at the table with the data scientists who are building these models.”
Executives identified current customer demand as largely prioritizing data quality over cost, decreasing the relevance of aggressive price competition in their fastest-growing relationships.
Senior Vice President Pendharkar confirmed ongoing momentum with the company’s largest customer and an “incredible pipeline of opportunity” extending beyond current forecasts.
Industry glossary
Agentic AI: Artificial intelligence systems designed to operate autonomously in dynamic, real-world environments, executing complex, multi-step tasks—often deployed in robotics or embedded edge devices.
LLM: Large Language Model, a deep learning algorithm trained on expansive text datasets to understand, generate, and manipulate human language for a variety of AI tasks.
Frontier model post-training data: Datasets specifically used to further customize, fine-tune, or evaluate high-performance AI models after initial training, with an emphasis on real-world relevance and accuracy improvements.
SOW: Statement of Work, a contractual document detailing the specific deliverables, scope, and terms for complex projects between service providers and clients.
Simulation data services: Custom data creation processes that replicate realistic or synthetic environments to train and validate AI and robotic systems in lifelike or anticipated scenarios.
Full Conference Call Transcript
Operator: Good day, ladies and gentlemen, and welcome to the Innodata Inc. Report Second 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. At any time during this call, you require immediate assistance, please press star followed by the number 0 for your operator. This call is being recorded on Thursday, 07/31/2025. I would now like to turn the conference over to Amy Agress. Please go ahead.
Amy Agress: Thank you, Sergio. Good afternoon, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, CEO of Innodata Inc., and Marissa Espineli, Interim CFO. Also on the call today is Aneesh Pendharkar, Senior Vice President of Finance and Corporate Development. We will hear from Jack first, who will provide perspective about the business, and then Marissa will follow with a review of our results for the second quarter. We will then take questions from analysts. Before we get started, I would like to remind everyone that during the call, we will be making forward-looking statements which are predictions, projections, and 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 and the risk factors section of our 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 reconciliations of these measures with comparable GAAP measures. Thank you. I will now turn the call over to Jack.
Jack Abuhoff: Thank you, Amy, and good afternoon, everyone. Thank you for joining us. We are very pleased to report that Q2 2025 was another outstanding quarter for Innodata Inc. We beat analysts' expectations across the board on key metrics: revenue, adjusted EBITDA, net income, and fully diluted EPS. Revenue grew 79% year-over-year, to $58.4 million, and adjusted EBITDA grew 375% to $13.2 million, reflecting the operating leverage that's inherent in our model. We also continue to strengthen our balance sheet. Cash increased from $56.6 million at the end of Q1 to $59.8 million at the end of Q2, and a few days after quarter close, we collected an $8 million payment that typically would have been received by June 30.
Our $30 million credit facility remains undrawn, giving us flexibility to support future growth. Our business momentum continues to accelerate. As a result, we are raising our full-year 2025 revenue growth guidance to 45% or more organic revenue growth, up from the 40% we communicated last quarter. Our forecast reflects significant new deals that have been finalized since our last call, as well as several deals that we believe are highly likely to close in the near term. We have a robust pipeline that includes significant dollar values, positioning us for a strong second half of the year. Many of these deals are not incorporated in our forecast, leaving room for possible further increases.
Demand for our services is strong and accelerating, and we are seeing success across a diversity of existing and new customers. I will talk about our largest customer first. We recently won several new projects with our largest customer, and we have others in the pipeline that are not yet included in our forecast but which we think are reasonably likely. Several of these new projects are under the second SOW we reported signing with this customer last quarter. We believe that the second SOW potentially gives us access to an even larger generative AI revenue pool with this customer.
With another big tech customer, we were recently awarded a number of significant engagements, and we have additional significant engagements in the late-stage pipeline, enabling us to forecast $10 million of revenue from this customer in the second half of this year. It is worth noting that we did just $200,000 of revenue with this customer over the entire trailing twelve-month period, so this is a very significant upswing that we believe will inure to our benefit significantly next year. These are just two examples. There are more. The traction we are now seeing is exhilarating. We have built a marquee set of customers whose trust we have worked hard to earn and whose demand for our capabilities is expanding.
Our big tech customers are in an all-out race towards superintelligence and autonomy, which we believe will be driven to a large degree by high-quality complex training data. We believe we are ideally situated to supply them with this high-quality complex training data. Moreover, we believe we are ideally situated to help them test models, diagnose performance issues, and prescribe data mixes required to improve performance. This is a frontier area. We believe that the future of LLM improvements lies not only in scale data but in smart data, knowing exactly what kinds of post-training data are required to achieve specific improvements in factuality, safety, coherence, and reasoning.
At the same time, we are positioning ourselves to help enterprises build and manage AI that can act autonomously, often referred to as agentic AI. This will require simulation training data to capture how humans solve multivariate problems. It will also require sophisticated trust and safety monitoring and management. We believe agent-based AI is going to serve as the cornerstone technology that unlocks the full value of large language models and generative AI for enterprises. Moreover, we believe that progress on agentic AI is likely to soon result in a ChatGPT moment for robotics.
Within the next several years, we believe agentic AI will be served at the edge in hardware devices with which we will commonly interact in many respects in our lives. We believe the market for simulation data services and evaluation services to drive agentic AI and robotics is likely to dwarf the market for frontier model post-training data. Our growth opportunities are significant and multidimensional. We intend to invest in ways that we believe will enable us to continue our growth path over the next several years. These include short-cycle high-return growth initiatives like custom annotation pipelines, verticalized agent development, and expanded global delivery. Strategic platform development, especially for LLM testing, safety, and real-world deployment.
Also, advisory and integration services for enterprises building AI-native systems. Expansion into new domains such as multi-agent and robotics, and expansion into new markets. We believe now is the time to lean in, investing in capabilities that can compound value over the next decade. This year, we intend to substantially increase investments, most of which will be expensed while at the same time beating 2024 adjusted EBITDA. In the second quarter, we incurred approximately $1.4 million of operating expenses that we think of as investments. This largely consisted of new hires in delivery, product innovation, go-to-market expansion, and talent acquisition. At the heart of this performance is a simple truth.
We are deeply aligned with the most significant technological invention of our era, generative AI. Across the entire life cycle of generative AI model training, from pretraining to post-training to evaluation to safety, we are delivering the services that unlock the performance of GenAI models. I will now turn the call over to Marissa to go over the financial results, after which Marissa, Aneesh, and I will be available to take questions from analysts.
Marissa Espineli: Thank you, Jack, and good afternoon, everyone. Revenue for Q2 2025 reached $58.4 million, representing a year-over-year increase of 79% and demonstrating strong continuing momentum. Adjusted gross margin was 43% for the quarter, up from 33% in Q2 of last year. Our adjusted EBITDA for Q2 2025 was $13.2 million or 23% of revenue, compared to $2.8 million or 9% of revenue in the same quarter last year. Net income was $7.2 million in the second quarter, up from a loss of $14,000 in the same period last year. In Q2, we were able to utilize the benefit of accumulated net operating losses or NOLCO to partially offset our tax liability.
Looking ahead to the coming quarters, barring any changes in the tax environment, we expect our tax rate to be approximately 27 to 28%. Our cash position at the end of Q2 2025 was $59.8 million, reflecting a sequential increase of about $3.2 million, shaped by strong profitability and disciplined cash management. As Jack mentioned, we collected an additional $8 million in early July that in the ordinary course would have likely been collected in Q2. We still have not drawn down on our $30 million Wells Fargo credit facility. The amount drawable under this facility at any point in time is determined based on a borrowing base formula.
I will reiterate what Jack said: The momentum in our business is nothing short of amazing. We believe we have got a tiger by the tail, and we are investing with a goal of positioning the company to align with what we project the market needs are going to be over the next few years. In Q2, we incurred approximately $1.4 million of operating costs to build out a variety of technical capabilities to expand our go-to-market as towards a future that we believe is truly exciting. Thank you, everyone. Sergio, we are ready for questions.
Operator: Thank you. Ladies and gentlemen, we will now begin the question and answer session. Should you have a question, please press star followed by the number one on your touch-tone phone. You will hear a prompt that your hand has been raised. Should you wish to decline from the polling process, please press the star followed by the number two. If you are using a speakerphone, please lift the handset before pressing any key. One moment, please, for your first question. Your first question comes from George Sutton from Craig Hallum. Please go ahead.
George Sutton: Thank you, team. Nice results. Congratulations. So I wondered if we could talk about during the quarter, your largest competitor, Scale AI, was a large majority purchased by Meta. And we have had a few of the large tech companies come out and say they would no longer work with Scale AI. These extensively would be tech companies that you have statements of work with. So I am just curious if you can kind of give us the after effect of that acquisition as you have seen it.
Jack Abuhoff: Hi, George. Well, thank you. Thank you for being on the call. So I guess, first, we congratulate Scale for having delivered a great success for their shareholders. And we believe their success and their valuation is a proof point of the, you know, the key role that data plays in model performance and the path towards superintelligence. You know, we compete with them successfully. And, you know, we believe that their shift in focus is likely to accelerate market opportunity for us.
George Sutton: Let us think about it a little more holistically. So they obviously were working with major tech companies. How quickly should we start to see that business shift? So if, for example, OpenAI comes out and says we are no longer going to be working with them, does that shift very quickly, and how do you go to market differently or more aggressively given the opportunities that will get created?
Jack Abuhoff: So I think even before this, you know, we were continuing to, you know, very aggressively outreach to market participants and to market our capabilities. You know, we have, in light of this, stepped up that effort with certain companies. And there are certain conversations that are going on, and are now planned to be happening over the next couple of months that I think, you know, could be very exciting for us. I do not know that I can get into particulars much beyond that. But, you know, I will reiterate that we do see an opportunity to, you know, accelerate our market presence.
George Sutton: Okay. And lastly for me, you threw out a nugget about robotics and the attachment to hardware, creating significant even more significant opportunities than the large language model training. So can you just walk through how you envision that would work for you and just lay out that opportunity?
Jack Abuhoff: Sure. So I think that, yeah, we tend to, you know, read about these technologies somewhat as if they exist in isolation. But the reality is that as large language models become, you know, more and more competent and able to interpret ambiguous language and, you know, have capabilities to plan and articulate, you know, multistep responses to problems. You know, there are technologies that will be added to that capability. Enabling those models to invoke external APIs or other tools, enabling for multistep tasks using either greater memory and planning capabilities. But when you take that, and then you think about deploying that at the edge within devices, what you have is a very capable robot.
So I think what this means for us is there is a whole new set of activities both to train these devices, to fine-tune models, and to evaluate their performance that together constitutes a market that I believe will exceed that of post-training data and evaluating models for frontier model builders. It is something we are hugely excited about and intend to be investing very significantly in. Perfect.
George Sutton: Thank you.
Jack Abuhoff: Thank you, George.
Operator: Your next question comes from Allen Klee from Maxim Group LLC. Please go ahead.
Allen Klee: Yes. Good afternoon. So when you reported last quarter, you kind of said that you thought revenue might be down around 5% in the second quarter. Your actual number was flat, up very slightly sequential. So you outperformed. So I am kind of curious like, where did the variance come from?
Jack Abuhoff: Sure. I will start, and then, Aneesh, if you want to give any additional color. I think that, you know, what we were trying to communicate last quarter is, you know, revenue was up. We were up on a run rate basis from our largest, and we were, of course, very happy about that. But we wanted to focus our investors on the guidance that we were giving because there are a lot of, you know, pluses, you know, quits and takes that get factored into that guidance. And underlying the work that we are doing, there are dependencies on engineering teams that we are working hand in glove with.
So it is entirely possible that a quarter could be up or down and that is not necessarily something that should be extrapolated out and considered, you know, locked and loaded permanently. We were not anticipating that it would necessarily be down, though, and we are very happy to see that it was not. You know, as I said, you know, looking at the largest customer and well as well as several quite a number actually of other customers, we see an incredible pipeline of opportunity right now. We are very excited about that.
And, you know, we are only baking into our guidance and our forecast things that we think are highly likely to close within the next, really, thirty to sixty days. There is a lot beyond that. I think we are going to be winning as well. So hope that is helpful. Aneesh, anything you want to add to that?
Aneesh Pendharkar: Yeah. I think you framed that correctly, Jack. And just to kind of reiterate, Allen, you know, we are not seeing any slowdown with our largest customer. You know, in Q2, we generated approximately $33.9 million of revenue from this account. And as Jack mentioned, you know, we secured several new projects and have additional opportunities in the pipeline that, while not yet included in our forecast, feel reasonably likely. So, again, we feel very bullish and optimistic about, you know, our prospects in the back half of the year and, you know, remain very excited.
Allen Klee: Thank you. You highlighted one of the things you highlighted was enterprise and the opportunity there. There are a lot of enterprises out there. I am just curious how you think about the go-to-market to attack it.
Jack Abuhoff: Yeah. It is a great question. Well, we are attacking it already. And, you know, what we are finding is that the interest in the technology and the opportunities to, you know, instantiate it into, you know, workflows exist across markets. So, you know, NAT we are looking at the markets where we have the most penetration and the most relationships today. But we are also reaching out to companies in markets where we do not have as much reach. And we are finding great, you know, receptivity. So I think the highlight there is that agentic AI, as it is proven, is going to be the catalyst that unlocks enterprise opportunity.
And I think that, you know, among enterprises that I talked to and, you know, more broadly, you know, they are no longer just looking at this like a frontier technology that is interesting to monitor. They are seeing it as, you know, new economic infrastructure. That they are going to need to be embracing. They are going to, you know, need to be adopting. And I think that we can play a very significant role in that.
When we have conversations with them about the things that we think they need to do and our consultants are working with them to figure out what is the right order of operations and how they gain control of their data in order to, you know, harvest these opportunities. We have got a lot of experience both from working with the large, you know, big techs on the frontier model such that we know where things are going and how they can best utilize them and also on all the work we have done historically, taking apart workflows and thinking about how to integrate new technologies into workflows to make them more efficient.
So yeah, super excited about the opportunities there. That is great. I will ask one more, and then I will jump back in the queue.
Allen Klee: You highlighted a certain amount of money this quarter. Spent that you operating expenses that you viewed as, like, investment. Is there any reason to think that the scale of how much you are going to be investing for growth in the second half is going to change meaningfully from where it has been?
Aneesh Pendharkar: Yeah. No. Great question, Allen. So we, as you probably pointed out, we said we invested about $1.3 million in Q2 across several functional areas, sales, delivery, and product solution capabilities. We anticipate stepping that up from Q2 to Q3 by approximately another and a half billion dollars. And the reason for doing that is we see tremendous opportunity in the space, and we want to be able to capitalize on that. So we will be making some incremental investments in sales, delivery, solutioning, and product to be able to, you know, capitalize on what we think are the very significant opportunities right now. Great. So congrats. Thank you.
Jack Abuhoff: Thank you.
Operator: Next question comes from Hamed Khorsand from PWS Financial. Please go ahead.
Hamed Khorsand: Hi. So my first question was could you just talk about why you mentioned organic growth and what your intentions are there?
Jack Abuhoff: Sure, Hamed. I think we mentioned it to draw attention to the fact that this is organic growth. You know, I think if you look across companies who are reporting and reporting growth, a lot of them are growing, you know, inorganically, and that can be a great strategy for them. But it is a different strategy. And I think our strategy and the kind of growth that we are reporting is testament to, you know, the product set and the capabilities that we have developed. And from a risk-adjusted basis, I think that is probably a safer bet for investors. So, you know, we are very proud of it.
We are, you know, we are very proud of what we have been able to accomplish and looking ahead to, you know, how well aligned we are with what we, you know, see as today's market and tomorrow's likely market opportunities, we think that organic growth can continue.
Hamed Khorsand: And the organic growth that you are seeing in your business, is that coming with any kind of competitive pressures on pricing? Or are you able to maintain pricing and capture new customers?
Jack Abuhoff: Well, you know, it is a robust market. I think that we expect, well, we are not just, we expect, we do experience, of course, a competitive environment. But what we are seeing is that the most important thing to our customers is not our price. It is the quality of our data. And the extent now to which we can work hand in glove with them in order to help understand model performance, understand model deficiencies, understand use cases, and make recommendations about the datasets that are required to remediate or to extend those capabilities. So it is a holistic service. And the investments that they are making are so extraordinary.
And there is such a deep desire to win in this race that when we are contributing as well as we are in so many accounts, they become much less price sensitive. Now that having been said, I do not believe that we are the most expensive among our competitive set, but I do think we are among the best. And that is a position that I think if we can sustain, that will significantly inure to our benefits from a competitive perspective and a growth perspective.
Hamed Khorsand: And lastly, last quarter, you had a series of different customers you were describing and talking about. This quarter, I think sounds a little less. So I am just trying to understand where are you in terms of those relationships? Have they started up what you were talking about last quarter? And, you know, so, you know, where do you sit as far as revenue opportunity goes when you look out into, you know, year-end '26?
Jack Abuhoff: Yeah. No. There is actually more opportunity in this bigger pipeline today than there was a quarter ago. You know, I just looked at that earnings call and thought that maybe that was a little long. And decided stylistically to trim it a bit. There is more opportunity. There are things that we talked about last time that have closed and that are now in our forecast. There are things that we are continuing to progress that are really interesting. By memory, I am thinking about things we talked about. I think there is only one thing where that kind of went dormant a little bit.
But everything else is either closed, moving forward well, advancing significantly in discussions, and that we feel very bullish about.
Hamed Khorsand: Very good. Thank you.
Operator: Thank you. Your next question comes from Mr. Allen Klee from Maxim Group LLC. Please go ahead.
Allen Klee: Oh, hi. I just had a follow-up. I thought it was really interesting how you said that you can make the data smarter for the customers to get better results. Could you go into that a little bit? Thank you.
Jack Abuhoff: Sure. So there are a lot of different dimensions that we use to look at data and analyze data. Our data science team is rapidly expanding. We end up, for engineering teams, producing what are the equivalent of, in many cases, the equivalent of white papers. With all sorts of, you know, mathematical formula and statistical analysis that correlate what we benchmark as a model performance or, you know, identify as a model's deficiency, what datasets are required in order to remediate that.
And what that capability has resulted in is that we are no longer just providing data, but our status, our role has been elevated to, you know, sitting at the table with the data scientists who are building these models and figuring it out with them. You know, the journey is about data, and it is about, as I, you know, in prepared remarks, it is about not just scale data, but smart data. So being able to do all that, you know, deep technical scientific analysis of data, of model performance, of correlating the data that is required in order to achieve the level of performance that is required.
In just the last, you know, I would say several months, that has become a problem space that we are getting to occupy. And that is tremendously exciting for us.
Allen Klee: Okay. Great. Thank you so much.
Jack Abuhoff: Thank you.
Operator: There are no further questions at this time. I will now turn the call over to Jack Abuhoff for closing remarks. Please go ahead.
Jack Abuhoff: Thank you, operator. So Q2 was a high-performing quarter with 79% year-over-year growth. And we are anticipating a strong second half to the year. In the second half, we anticipate potentially winning major new customers, significantly deepening relationships, and further broadening our base. We will also be continuing to make investments in infrastructure, talent, and platforms that we believe are key to continuing our growth trajectory over the years to come. As a result of our successful execution, we are raising our guidance today from 40% to 45% or more organic revenue growth for the year.
And, yeah, I mean, we are humbled by our good fortunes that scale data, our specialty is, we believe, the cornerstone of the greatest technological innovation of our lifetimes. And, you know, with the runway we see ahead, our goal remains to build Innodata Inc. into one of the leading AI services companies for this era. So, you know, thank you all for your continued support. And, you know, we will look forward to being with you a quarter from now.
Operator: Ladies and gentlemen, this concludes today's conference call. Thank you for your participation. You may now disconnect.