Snorkel Raises $350 Million at $3.5 Billion Valuation
Snorkel AI raised its valuation to $3.5 billion after gathering $350 million, expanding its platform that builds and evaluates the data used to train frontier models.

Snorkel AI has raised $350 million in a new funding round, pushing its valuation to $3.5 billion, according to a pre-market opening update reported by the New York Stock Exchange on October 7. The disclosure came as part of a pre-market update distributed by the NYSE via PR Newswire. The company works on a data development platform relied upon by AI labs and enterprises.
The platform is used to prepare data behind evaluating and training frontier models, an increasingly vital area as companies compete on data quality rather than volume. The update noted that the company aims to expand its platform, without revealing the names of the investors participating in the round.
In accompanying remarks, CEO Alex Ratner said that advancing data science and technology "will be considered one of the most impactful research areas in AI." Ratner was scheduled to appear on a live stream from the NYSE to explain his vision, according to the same update, which contained no other direct quotes.
This comes as investors pour significant capital into the data and model layer, where securing high-quality data for evaluation and training has become a decisive factor among competitors, as the cost of building models themselves has receded compared to the cost of preparing their data.
What do these terms mean?
Funding Round: A phase in which a startup raises capital from investors in exchange for an equity stake. Early rounds are named Series A, then B, then C, depending on the company's progress.
Company Valuation: The estimated market value of a company after a round, representing the figure agreed upon by investors to determine the price per share, not necessarily liquid cash held by the company.
Frontier Models: The most powerful and cutting-edge AI models operating at the edge of technological capabilities, making performance evaluation and testing more complex.
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