Instead of signing expensive contracts with companies for their data, AI labs these days are trying a new way: tapping former senior employees from those companies for their industry knowledge, Mercor CEO Brendan Foody said at TechCrunch Disrupt 2025 on Tuesday.
Speaking at a panel on stage, Foody touted Mercor’s marketplace as one of the main channels connecting former employees of investment banks, consultancies and law firms with AI labs looking to automate those industries. Some of Mercor’s customers include OpenAI, Anthropic and Meta.
“There’s an argument that Goldman Sachs doesn’t like the idea of having models that are able to automate their value chain,” Foody said, using the Wall Street giant as an example. “It certainly changes the competitive dynamic, and that’s one reason labs need us. Their customers don’t want to give them data to automate large portions of their value chains, so they need to hire contractors who previously worked at those companies, understand those workflows, and are willing to train models to automate them.”
Foody, the 22-year-old co-founder of Mercor, says his startup pays industry experts up to $200 an hour to fill out forms and write reports for AI training. The company now has tens of thousands of contractors and says it grants them more than $1.5 million every day. However, Foody says the startup remains profitable because AI labs are willing to pay even more for this valuable data.
In less than three years since its inception, Mercor has grown its annual recurring revenue to approximately $500 million and recently raised funding at a $10 billion valuation.
Incumbents across the economy have good reason to resist Mercor’s rise, as their industry knowledge may be leaking out the back door via ex-employees in the startup’s market, which could eventually be used to automate their work. Foody acknowledged that it may be exposing an inefficiency in the market, but said he wouldn’t call it a “loophole.”
In fact, Foody says some companies are already embracing this “new future of work.” He entertained the idea that buying Mercor could create a new type of gig economy, as Uber did more than a decade ago. (Earlier this year, former Uber chief product officer Sundeep Jain joined Mercor as president.)
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“There are companies that are embracing it and realizing that the world is going to change very quickly,” Foody said. “There’s definitely another category of companies that are afraid and worried about being disintermediated and that their customers are going directly to the AI labs or the application layer platforms. My belief is that the former category will turn out to be on the right side of history.”
While Mercor tries to draw knowledge from various industries, Foody said his startup is trying to prevent contractors from committing corporate espionage — the illegal act of stealing proprietary information, trade secrets or intellectual property from one business and selling it to another.
But that’s easier said than done. Most of Mercor’s workforce are former employees of law firms, investment banks and other industries that are very secretive about their data. Foody said some of Mercor’s contractors are still working at their day jobs and are just submitting data from their side, and claimed contractors are being instructed not to upload documents from their former workplace. However, he acknowledged that it’s possible “there are things going on” given the scale of his startup.
Foody argues that the knowledge in an employee’s head belongs to the employee, not their company — a more generous view than many businesses would take. Additionally, in some of Mercor’s job postings, the startup walks the line between requesting an employee’s knowledge and their company’s data.
For example, Mercor is currently looking for CTO or co-founder of a startup which “can authorize access to a substantial production codebase” for AI evaluations or potentially AI model training. In an email, Mercor told TechCrunch that some of its startup CTOs have accepted this offer, but declined to disclose details of their contracts.
Mercor was one of the first data startups to hire highly skilled workers in the US and pay them large sums to train AI models. Early in the AI boom, data vendors like Scale AI hired contractors in third-world countries to do fairly simple tagging tasks. Now, most of Mercor’s competitors — including Surge and Scale AI — have realized that AI labs need experts to improve their AI models. Many data vendors have also begun training “environments” to improve the ability of AI agents to complete real-world tasks.
Mercor has clearly benefited from Scale AI’s mishaps: Many AI labs stopped working with Scale AI after Meta made a big investment in the startup and hired its CEO. In the past year, Mercor has quintupled in value, but still remains smaller than Surge and Scale AI, which are worth more than $20 billion.
Today, most of Mercor’s revenue comes from just a few AI labs, but Foody says the startup plans to work with other industries in the future. He believes legal, financial and medical companies will want help leveraging their data to train AI agents – something Mercor specializes in.
“Over time, ChatGPT will be better than the best consulting firm, better than the best investment bank and better than the best law firm,” said Foody. “This will fundamentally transform the economy, which will be a generally positive force that helps create abundance for all.”
