The Mercor Series D round raised $750 million at a $20 billion valuation, the AI training company said on November 10, doubling its value in about a year. Mercor, which pays experts to teach frontier models, drew in Nvidia and Salesforce alongside a long list of venture firms, and the round included an employee tender.
The Mercor Series D lands as the market for human expertise to train AI has become one of the most valuable corners of the AI economy. Mercor began as an AI-powered hiring platform and now connects technology companies with subject-matter experts whose knowledge is used to train, test and improve AI models and agents. Its network counts more than five million experts paid to train frontier models, according to the company.
Who Backed the Mercor Series D
The round drew participation from Benchmark, Felicis, Fundomo, funds managed by affiliates of Apollo, G Squared, General Catalyst, Glade Brook Capital, Nvidia, Salesforce, Sapphire Ventures, StepStone Group, XTX Ventures and Zoom, Mercor announced. General Catalyst had been reported in August to be in talks to lead the round.
The new mark doubles Mercor’s last priced round. The company raised $350 million in October 2025 at about a $10 billion valuation, Reuters reported, and it is backed by Jack Dorsey and venture capitalist Peter Thiel. Revenue has grown more than five times since September 2025, co-founder and chief executive Brendan Foody told Sourcery in an interview published with the announcement, and the company now pays out more than $5 million a day to people helping train frontier AI models.
What Mercor Does With the Money
Mercor said the funding will accelerate its evaluation and post-training business, giving companies a way to measure and set standards for how reliably AI agents complete tasks and at what cost. The money will fund infrastructure and research for evaluations and post-training, and more environments where agents can learn complex workflows.
That work already reaches beyond the frontier labs. Mercor says the capabilities it built for model builders are now being adopted by big tech companies, developers of open models, application-layer companies and the Fortune 500. The company opened offices in New York and London in 2026, expanding beyond San Francisco to sit closer to enterprise and laboratory customers.
From Hiring Platform to AI Training Infrastructure
Mercor was founded in 2023 by Brendan Foody, Adarsh Hiremath and Surya Midha, three Bay Area high school friends who started out building an AI-powered hiring platform. The pivot to training data followed the labs’ demand for expert human knowledge: every job in the economy needs its own agents, Foody wrote in the announcement, and professional work depends on two kinds of knowledge no model inherently has, how a task gets done and how a specific company does it according to its systems, policies or quality bar.
The company acquired Deeptune earlier this year, a reinforcement-learning environment company whose team spent two years recreating hundreds of enterprise applications, from spreadsheets to Salesforce, where AI agents can practice professional workflows. “We give every enterprise the data and evaluation needed to make those models their own,” Foody wrote, adding that “AI is only as useful as the human expertise behind it.”
Why It Matters
The round is a marker for where AI investment is flowing. According to Crunchbase, AI-driven startups raised $102 billion, or 64% of global venture capital, in the third quarter of 2026, and Mercor sits at the center of the bottleneck that money is chasing: models can only get better at real work if someone who does that work teaches and tests them. Mercor’s own economics underline the point. The company says it already spends three times as much on inference as on employee salaries, and it argues that if that ratio holds as AI spreads through the economy, it points to double-digit GDP growth over the next five years, nearly three times the usual rate.
For the labs, the deal also deepens a strategic relationship. Nvidia, a participant in the round, supplies the hardware that trains the models Mercor’s experts teach, and the company’s evaluation and post-training work now feeds both frontier labs and the enterprises trying to put agents into production. The $20 billion valuation makes Mercor one of the most valuable private AI infrastructure companies, and Foody has said the ambition is to build a trillion-dollar business.
