Mercor.io Corp., a leader in artificial intelligence training data, has secured $750 million in a Series D funding round, valuing the company at $20 billion. The company aims to broaden its reach from frontier AI labs to enterprises across various industries.
Mercor's co-chief executive, Brendan Foody, emphasized the necessity for businesses to develop their own AI agents, asserting that every job in the economy will eventually require one. The company has spent the last two years collaborating with frontier labs to build the necessary infrastructure. Foody noted that Mercor's annualized revenue exceeded $2 billion as of June, highlighting the rapid growth of their lab business.
Adarsh Hiremath, the other co-chief executive, pointed out the limitations of public benchmarks for AI models. He explained that a model might perform well on these benchmarks but fail to meet the specific systems and policies of individual businesses. To address this, Mercor creates custom benchmarks for each enterprise client, ensuring the AI models align with the company's standards.
The funding round saw participation from a diverse group of investors. Notable contributors included Nvidia Corp., Salesforce Inc., and Zoom Communications Inc., alongside returning investors like Benchmark Capital Management Co., Felicis Ventures Management Co., and General Catalyst Group Management. Other investors in the round were Fundomo, G Squared Equity Management LP, Glade Brook Capital Partners, Sapphire Ventures, StepStone Group Inc., XTX Ventures, and funds managed by affiliates of Apollo Global Management Inc.
Mercor's previous funding round, a Series C led by Felicis in October 2025, raised $350 million and valued the company at $10 billion. The latest round included a tender offer for employee shares, although the company has not disclosed how the $750 million is divided between this offer and new capital.
Mercor's acquisition of Deeptune Inc. in July has been pivotal in enhancing its capabilities. Deeptune's team had spent two years developing enterprise applications for AI agents to practice on, which Mercor plans to expand with the new funds. This acquisition supports Mercor's strategy to provide tailored post-training environments for enterprise clients.
Frontier labs have been the primary consumers of Mercor's expert-driven training data. However, the company anticipates a shift as open models become sophisticated enough for enterprise use. Mercor's extensive work with labs has created a unique offering that is difficult to replicate.
