"Mercor, which connects AI labs with domain experts for training their foundational AI models, has raised $350 million at a $10 billion valuation, the company confirmed to TechCrunch. Felicis Ventures, which led the company's previous $100 million Series B at a $2 billion valuation, is also leading this round. Existing investors Benchmark and General Catalyst, and new investor Robinhood Ventures also participated."
"Mercor started off as an AI-driven hiring platform but quickly pivoted to providing companies with specialized domain experts to perform AI model training - such as scientists, doctors, and lawyers - and charging an hourly finder's fee and matching rate for their work. The company has also been adding more software infrastructure for reinforcement learning - a training method where a model's or agent's decisions are verified or disputed, enabling it to incorporate feedback and improve over time."
Mercor raised $350 million at a $10 billion valuation with Felicis Ventures leading the round and participation from Benchmark, General Catalyst, and Robinhood Ventures. Mercor pivoted from an AI-driven hiring platform to matching domain experts—scientists, doctors, and lawyers—with AI labs for model training, charging hourly finder's fees and matching rates. The company is expanding software infrastructure for reinforcement learning to incorporate verified feedback and improve models over time. Mercor plans to build an AI-powered recruiting marketplace and believes market shifts involving other data-labeling vendors have created growth opportunities. The company projects rapid ARR growth toward $500 million.
Read at TechCrunch
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