Deccan AI Raises $25M to Take On Mercor in the AI Talent War

Behind every polished AI model you use today — every coding assistant, every chatbot, every reasoning engine — there is an invisible army of human experts training it, evaluating it, and fixing its mistakes. That industry is booming. And one startup is moving fast to claim a larger share of it. Deccan AI — a startup supplying post-training data and evaluation work — has raised $25 million in its first major funding round, with much of that work carried out by an India-based workforce of domain experts. The all-equity Series A round was led by A91 Partners, with participation from Susquehanna International Group and Prosus Ventures. At digital8hub.com, we've been tracking the rise of the AI post-training economy since its earliest days. Today's raise puts Deccan AI firmly on the map — and signals a new phase of competition in a market that has suddenly become one of the hottest in all of tech. What Does Deccan AI Actually Do? Deccan AI sits at a critical — and often overlooked — layer of the AI value chain: post-training. While frontier AI labs including OpenAI and Anthropic build core models in-house, much of the post-training work — from data generation to evaluation and reinforcement learning — is increasingly being outsourced as companies push to make systems reliable in real-world use. Founded in October 2024, Deccan provides services ranging from helping models improve coding and agent capabilities to training systems to interact with external tools such as APIs, which connect AI models to software systems. Think of it this way: OpenAI or Google builds the brain. Deccan AI helps teach it to think clearly, avoid mistakes, and behave correctly in the real world. That last step — post-training — is where the difference between a good AI model and a great one is made. And it requires enormous volumes of high-quality, human-verified data, produced quickly and accurately by domain experts. The India Advantage — And Why It's Deliberate Even as its customers are largely US-based AI labs, most of Deccan's contributors are based in India. Competitors such as Turing and Mercor also source contractors from the country, but operate across a broader set of emerging markets. Deccan chose to concentrate much of its workforce in India to better manage quality. "Many of our competitors go to 100-plus countries to find the experts," CEO Rukesh Reddy said. "If you have operations in just one country, it becomes far easier to maintain quality." This is a deliberate strategic bet — and one that has clearly paid off so far. Indians are increasingly being tapped to fill expert roles in STEM, humanities, and other fields by companies training AI models. In return, contributors get competitive pay, flexible working hours, and a chance to upskill in one of the fastest-growing industries on the planet. About 10% of Deccan's contributor base holds advanced degrees such as master's and PhDs, with that share rising significantly on high-complexity projects. Deccan has also begun sourcing niche talent from the US for specialised domains including geospatial data and semiconductor design. The Numbers That Made Investors Pay Attention Deccan AI is not a concept-stage startup chasing funding on the strength of a pitch deck. It is a business with real, rapidly growing revenue — and the numbers tell a compelling story. Deccan grew 10x over the past year and is now at a double-digit million-dollar revenue run rate. About 80% of its revenue comes from its top five customers, reflecting the concentrated nature of the frontier AI market. A 10x revenue growth rate in twelve months is the kind of trajectory that gets serious investors moving fast. A91 Partners — the lead investor — is one of India's most respected growth-stage venture funds, and the participation of Prosus Ventures and Susquehanna International Group signals broad confidence in the thesis. The Quality Problem Nobody Has Solved At the heart of Deccan AI's pitch is a blunt acknowledgement of an uncomfortable truth about the industry it serves. "Quality remains an unsolved problem," CEO Rukesh Reddy said, adding that tolerance for errors in post-training is "close to zero" as mistakes can directly affect model performance in production. That makes post-training more complex than earlier stages of AI development, requiring highly accurate, domain-specific data that is harder to scale. The work is also highly time-sensitive — AI labs sometimes require large volumes of high-quality data within days — making it difficult to balance speed with accuracy. This is the core tension in the AI training services market — and it is the gap Deccan AI is specifically designed to fill. Speed without quality produces bad models. Quality without speed loses clients. Getting both right, at scale, is genuinely hard — and that difficulty creates the moat that Deccan is building its business around. Who Is Deccan AI Competing Against? The market for AI training services has expanded rapidly alongside the rise of large language models. Companies such as Meta-owned Scale AI and its rival Surge AI, as well as well-funded startups Turing and Mercor, compete to provide data labelling, evaluation, and reinforcement learning services to the world's leading AI labs. Mercor — the most direct comparator — is currently valued at $10 billion after raising a $350M Series C in October 2025 from Felicis Ventures and General Catalyst. Scale AI, now majority-owned by Meta following a $14 billion acquisition of a 49% stake, remains the dominant player in the broader data labelling space. That Meta-Scale deal created a significant window of opportunity for independent players. When Meta acquired Scale AI, both OpenAI and Google moved quickly to cut ties with the company — creating immediate demand for alternative providers. Competitors were quick to proclaim their independence, and Deccan AI has been among the fastest to fill the gap. India's Moment in the Global AI Economy Deccan AI's rise is part of a broader story about India's role in the global AI value chain — and that role is evolving rapidly. For now, India's position is primarily as a supplier of talent and training data rather than a developer of frontier models, which remain concentrated among a handful of US companies and a few players in China. But that framing is changing. As India produces more AI-native engineers, researchers, and domain experts, the country's contribution to the AI economy is moving steadily up the value chain. Startups like Deccan AI are part of that shift — building globally competitive businesses on the strength of India's deep, underutilised talent pool. For India's tech ecosystem, today's raise is more than a funding announcement. It is a signal that Indian-founded, India-powered AI companies can compete at the highest levels of the global market — and win. What Comes Next for Deccan AI? With $25 million in fresh capital, Deccan AI will almost certainly accelerate hiring, expand its contributor network, and deepen its relationships with the frontier AI labs that currently make up the bulk of its customer base. The concentration risk — 80% of revenue from five customers — is the most obvious challenge to address as the company scales. The AI post-training market is growing faster than almost any other segment of the technology economy right now. Every major AI lab in the world needs more high-quality training data, faster. The companies that can consistently deliver that — with zero tolerance for error — will be worth billions. Deccan AI just raised $25 million to prove it can be one of them. Stay across every development in AI, startups, and the technology economy at digital8hub.com — your trusted source for the stories that shape the digital world.