AI's Next Big Thing? Deccan AI Raises $25M, Taps India's Experts to Train Models

Deccan AI, a startup providing post-training data and evaluation work for AI models, has secured $25 million in its first major funding round. This Series A round, led by A91 Partners with participation from Susquehanna International Group and Prosus Ventures, underscores the growing interest in optimizing AI models.

The demand for services like those offered by Deccan AI is surging as companies seek to improve the reliability of AI systems in real-world applications. Founded in October 2024, the company offers services ranging from helping models improve coding and agent capabilities to training systems to interact with external tools such as application programming interfaces (APIs).

Deccan AI collaborates with frontier AI labs and also serves enterprises through products including its evaluation suite, Helix, and an operations automation platform, demonstrating a comprehensive approach to AI training.

Deccan AI's customers include Google DeepMind and Snowflake, which highlights its growing influence in the industry. The company has onboarded about 10 customers and runs a couple of dozen active projects at any given time, according to Rukesh Reddy, founder of Deccan AI.

The startup, headquartered in the San Francisco Bay Area with a large operations team in Hyderabad, India, employs about 125 people and relies on a network of more than 1 million contributors, including students, domain experts, and PhDs.

Deccan AI's focus on quality and specialization allows it to stand out in a competitive market, offering solutions that go beyond simple data labeling and focus on higher-skill and more complex tasks.

Deccan AI has chosen to concentrate much of its workforce in India to better manage quality, a strategy that differentiates it from competitors operating in multiple countries. According to Reddy, “Many of our competitors go to 100-plus countries to find the experts.”

This strategy highlights India's current position in the global AI value chain, as a supplier of talent and training data, rather than a developer of frontier models.

Deccan AI's business model, built as a “born GenAI” company, focuses on high-skill work from the outset, which has allowed it to achieve significant growth, multiplying its revenue by 10 in the last year.

The market for AI training services has expanded rapidly alongside the rise of large language models, with companies such as Meta-owned Scale AI and its rival Surge AI, as well as startups Turing and Mercor, competing to provide data labeling, evaluation, and reinforcement learning services.

Tolerance for errors in post-training is “close to zero” as mistakes can directly affect model performance in production, according to Reddy.

The sector has faced criticism over working conditions and pay, with large pools of gig workers often used to generate training data. Reddy said earnings on Deccan’s platform range from about $10 to $700 per hour, with top contributors earning up to $7,000 a month.

The work in the AI sector is also highly time-sensitive, with AI labs sometimes requiring large volumes of high-quality data within days, making it difficult to balance speed with accuracy.

Deccan AI focuses on quality and speed, crucial in the competitive AI market. Reddy said Deccan was built as a “born GenAI” company, in contrast to traditional data labeling firms that began with computer vision tasks. This means it has focused on higher-skill work from the outset.

Deccan AI has experienced significant growth and is now at a double-digit million-dollar revenue run rate, Reddy said, declining to share specifics. About 80% of its revenue comes from its top five customers, reflecting the concentrated nature of the frontier AI market, he added.