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 analyst 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 8 big tech customers we talked about recently on these calls, we are currently forecasting 6 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 the 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 evaluation 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 8 customers, we landed in Q3 or expect to finalize shortly 5 additional big techs. We believe all 5 of these new big techs are poised to contribute meaningfully to our 2026 growth. Three of these new 5, 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 2 of these are global leaders in commerce, cloud and AI. Now let's turn to our new 2025 initiatives, 6 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 pretraining data at scale. Now pretraining 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 pretraining data. Models that trained on higher-quality pretraining corpora 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 pretraining data. So we invested about $1.3 million to build new capabilities to create high-quality pretraining 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 5 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 pretraining 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 announced 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 the 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 life cycle, 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 that 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 3 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. Clarke, 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 and 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 million 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 that 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 task 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 multistep 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 6 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 start-ups that have raised tens of millions of 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 are 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 2 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 Clarke, who retired four-star Army General and former Commander of U.S. 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 5 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.