Data startup Snorkel AI has raised $350 million in fresh funding at a $3.5 billion valuation, its CEO Alex Ratner told Reuters, as booming demand from frontier AI labs for increasingly complex training data and simulated environments fuels rapid growth.

Led by Insight Partners and S32, the funding round included participation from existing investors Addition, Greylock and Wells Fargo, the company said. The deal values the company at nearly three times the $1.3 billion valuation achieved when it last raised $100 million in May 2025.

The San Francisco-based company said its annualized revenue run-rate has crossed $350 million, from roughly $20 million a year earlier, driven by the data-as-a-service business it launched in September 2025.

Founded in 2019 by a team of researchers spinning out of the Stanford AI lab, Snorkel AI initially sold software but has shifted toward supplying finished datasets and reinforcement-learning, or RL, environments directly to customers.

Ratner said demand had grown as AI developers moved beyond simpler labeling work and sought harder, higher-stakes data to train and evaluate increasingly capable systems.

Snorkel now offers what it calls an "agentic data development platform" that pairs human experts with thousands of specialized AI models and agents to create and vet data. Experts devise design scenarios, tasks and grading rubrics, while AI automates much of the labor-intensive quality assurance process, Ratner said, as it partners with AI labs to design ways to acquire high-quality datasets.

The business taps a network of tens of thousands of specialists across fields such as coding, law and medicine. Ratner said Snorkel sells the data products they generate rather than charging for human labor, a model that lets it pay experts more generously while preserving margins.

"Our strong view is that 100% of the data that labs will get value out of will have some human input in the foreseeable future," Ratner said. "But 100% of that data will have to use synthetic and automated approaches to keep up with this complexity."

The company says it works with frontier AI labs, hyperscalers, enterprises and the US federal government. Coding data is one of Snorkel's biggest areas of demand.

Venture funding continues to pour into startups supplying frontier AI labs with human-annotated training data, a market transformed after Meta's $14.3 billion purchase of a 49% stake in Scale AI in June 2025. Rivals including Mercor and Surge AI have also attracted investor interest amid strong revenue growth.

Ratner said the fresh capital would be used to hire researchers and engineers, while expanding the company's enterprise and government operations. The startup also plans to support third-party AI model evaluations and push into new industry verticals and data modalities.

While growth remains the priority, the company said it expects to reach profitability this year.

"Data is becoming more rare, more specialized, more difficult to find," said Andy Harrison, partner at S32 who co-led the funding. "If you want to train the most frontier, complex and capable models, now you need superior data."