The startup's revenue run-rate went from $20 million to $350 million in a year. Its pitch to investors is that frontier AI labs are running out of good data to train on, not good chips.
Data startup Snorkel AI has raised $350 million in a new funding round that values the company at $3.5 billion, nearly triple the $1.3 billion valuation it carried after its last raise in May of last year. The round was led by Insight Partners and S32, with participation from existing investors Addition, Greylock and Wells Fargo.
The company said its annualized revenue run-rate has climbed to roughly $350 million, up from about $20 million a year earlier, driven largely by a data-as-a-service business it launched in September of last year. Snorkel, founded in 2019 by a team spinning out of Stanford's AI lab, has shifted its business model over time from selling software tools to directly supplying finished training datasets and reinforcement-learning environments to AI developers.
Chief Executive Alex Ratner said demand has grown as AI developers move past simpler data-labeling work toward harder, higher-stakes data needed to train and evaluate increasingly capable systems. The company describes its offering as an "agentic data development platform" that pairs thousands of human subject-matter experts, in fields like coding, law and medicine, with AI models that automate much of the quality-review process; Snorkel says it sells the resulting data products rather than charging for the underlying human labor directly, a structure it says lets it pay experts more while preserving its own margins.
"Data is becoming more rare, more specialized, more difficult to find," said Andy Harrison, a partner at S32 who co-led the round. "If you want to train the most frontier, complex and capable models, now you need superior data."
The round lands amid a broader wave of venture funding into companies supplying frontier AI labs with human-curated training data, a market that reshaped after Meta's $14.3 billion purchase of a 49% stake in rival Scale AI last year. Snorkel says it expects to reach profitability this year even as it continues hiring researchers and engineers and expanding into new industries and data types, a rare combination of hypergrowth and near-term profitability among AI-infrastructure startups at this stage.