Mercor

Brendan Foodie and his co-founders started Mercor in January 2023 when they were just 19 years old. Initially, they built a recruiting platform—automating resume review, interviews, and hiring decisions using LLMs to help match international talent with opportunities. They bootstrapped the company to $1M in revenue run rate before dropping out of college. But the real inflection point came in August 2023 when an existing customer introduced them to the XAI co-founding team over Zoom, pitching them on finding "really smart Indian software engineers" for math and coding work.

That meeting changed everything. Within two days, they were at the Tesla office meeting the entire XAI co-founding team (minus Elon). XAI wasn't ready for human data yet, but Brendan knew the market was about to shift radically. "We didn't start working with them at that point," he recalls. "We just knew from that point forward...that the market was about to change radically and we needed to be at the frontier of that."

The next critical moment came in early 2024 when a major crowdsourcing player approached them wanting to hire over 1,000 people through their platform. The deal seemed like validation—until the support tickets started flooding in. "Those people weren't getting paid," Brendan explains. "We felt horrible." That crisis revealed a massive gap: the incumbent data labeling companies were optimizing for volume and cost, not quality or dignity. Meanwhile, the AI labs' needs had fundamentally shifted.

The wealthiest companies in the world—OpenAI, Anthropic, Google DeepMind—were no longer looking for cheap crowdsourced annotators. They needed extraordinary professionals: lawyers to evaluate contract redlining, radiologists to assess medical reasoning, software engineers to judge coding capabilities. They needed people who could write evals—essentially defining what success looks like for a model.

"The labs' primary bottleneck to improve models is how they can effectively measure what success looks like for the model," Brendan explains. This insight became their north star. In May 2023, they pivoted to working directly with the labs, cutting out middlemen and paying their expert network $95-$500/hour—a 3-16x premium over crowdsourcing rates.

The growth was staggering. "We grew from one to 400 million in revenue run rate in 16 months," Brendan states flatly. "Fastest ascent in history." By the time they raised their seed round from General Catalyst in September 2023, they were already at $1.5M in run rate. When they told Benchmark they'd hit $50M by year-end, the investors thought they were insane. Two weeks later, they'd done it.

Key to this success were three core values Brendan hammered into the culture:

**Can-do attitude**: Setting ridiculously ambitious goals and reorganizing the company around them. "We've always set these ridiculously ambitious goals and then somehow the trajectory of the company forms around those goals."

**High standards**: They hired former founders and exceptional operators—eventually bringing in Sundae Jane, ex-CTO and CPO of Uber, as president. They maintained brutal selectivity both in team composition and in the caliber of experts onboarded.

**Intensity**: An early-stage culture where people cared deeply about moving the frontier. Not mandated hours, but a natural output from finding people with ownership mentality. "It's much more about finding people of a lot of ownership and are really bought in."

They also remained zero in sales and marketing for 18 months, instead pouring 100% of resources into product and customer experience. The result: zero churn, 1600%+ net retention, and customers asking to keep working with them at other companies.

Mercor is now a $4.8B ARR business (based on their $400M monthly run rate) with customers across six of the Magnificent Seven tech companies and all five top AI labs. They never had a customer churn. They've raised $100M at a $2B valuation, making Brendan the youngest unicorn founder.

But for Brendan, the financial metrics are secondary to the mission: creating the future of work. "The narrative in AI over the last three years has almost entirely been one of job displacement. But very few companies have talked about this new category of jobs that's being created," he observes. While others fear AI will eliminate human work, Mercor is building the infrastructure for what comes next: a world where humans and AI collaborate at scale, and the bottleneck is finding enough exceptional people to teach models what excellence looks like.