Jack S. Abuhoff
Thank you, Amy, and good afternoon, everyone. Thank you for joining us. We're very pleased to report that Q2 2025 was another outstanding quarter for Innodata. 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 additional $8 million 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 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'll talk about our largest customer first. We recently won several new projects with our largest customer and we have others in 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 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 12-month period. So this is a very significant upswing that we believe will inure to our benefit significantly next year. These are just 2 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 at an all-out race towards super intelligence 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 process multivariant 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 systems 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're delivering the services that unlock the performance of Gen AI models. I'll now turn the call over to Mariss to go over the financial results, after which Mariss, Aneesh and I will be available to take questions from analysts.