As the demand for training and improving artificial intelligence models increases, Deccan AI — a startup that provides post-training data and evaluation work — has raised $25 million in its first major funding round, with much of that work being done by a workforce of experts based in India.
The all-equity Series A round was led by A91 Partners, with participation from Susquehanna International Group and Prosus Ventures.
While frontier AI labs including OpenAI and Anthropic build basic models, much of the post-training work—from data generation to evaluation and reinforcement learning—is increasingly outsourced as companies push to make systems reliable in the real world. Deccan is emerging as one of the new startups catering to this demand.
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 application programming interfaces (APIs), that connect AI models to software systems.
The startup works with frontier labs on tasks such as creating expert feedback, running assessments and creating supportive learning environments, while also serving businesses through products such as its assessment suite, Helix, and an operations automation platform. The project is also evolving as models move beyond text to so-called “world models” that better understand physical environments, including robotics and vision systems.
Deccan’s clients include Google DeepMind and Snowflake, according to the company. It has onboarded about 10 clients and runs a few dozen active projects at any given time, founder Rukesh Reddy (pictured above) said in an interview.
The startup, based in the San Francisco Bay Area with a large operations team in Hyderabad, employs about 125 people and relies on a network of more than 1 million collaborators, including students, domain experts and PhDs. About 5,000 to 10,000 contributors are active in a typical month, Reddy told TechCrunch.
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About 10 percent of Deccan’s partner base has advanced degrees, such as masters and PhDs, although the share is higher among active partners depending on project requirements, Reddy said.
The AI training services market has expanded rapidly alongside the rise of large language models, with companies such as Meta-owned Scale AI and its rival Surge AIas well as startups Turing and Mercor competing to provide data labelling, evaluation and reinforcement learning services.
“Quality remains an unsolved problem,” Reddy said, adding that tolerance for errors after training is “close to zero,” since errors can directly affect the model’s performance in production. This makes post-training more complex than previous stages, requiring highly accurate, domain-specific data that is more difficult to scale.
The work is also very time-sensitive, he said, with AI labs sometimes requiring large volumes of high-quality data within days, making it difficult to balance speed with accuracy.
The industry has faced criticism over working conditions and paywith large groups of gig workers often used to generate training data. Reddy said earnings on Deccan’s platform range from about $10 to $700 an hour, with top contributors earning up to $7,000 a month.
India is emerging as a hub for AI training talent
Although its customers are largely US-based AI labs, most of Deccan’s partners are based in India. Competitors such as Turing and Mercor contractors also come from the country, but operate in a broader set of emerging markets.
Deccan chose to center much of its workforce in India to better manage quality, Reddy said. “Many of our competitors go to more than 100 countries to find the experts,” he said. “If you have operations in just one country, it becomes much easier to maintain quality.”
This approach underscores India’s current position in the global AI value chain — as a supplier of talent data and training rather than a developer of cutting-edge models, which remain concentrated in a handful of US companies and a handful of players in China.
However, Reddy said Deccan has started sourcing talent from a few other markets, including the US, for specialized expertise in geospatial data and semiconductor design.
Reddy said Deccan was created as a “born GenAI” company, unlike traditional data tagging companies that started with computer vision work. This means it has been focused on higher skill work from the start.
Deccan has grown 10-fold in the past year and is now in the double-digit million dollar revenue range, Reddy said, declining to share details. About 80% of its revenue comes from its top five customers, reflecting the concentrated nature of the frontier AI market, he added.
