Snorkel AI has raised $350 million in Series E funding at a $3.5 billion valuation as demand grows for specialized datasets and simulated environments used to train and evaluate AI systems. The seven-year-old company says its annualized revenue run rate has reached $375 million, up 18-fold over the past 12 months.
Insight Partners and S32 led the round, with existing investors including Addition, Lightspeed, Greylock, GV and Wells Fargo also participating. The valuation is nearly three times the $1.3 billion Snorkel received when it raised $100 million in Series D funding 17 months ago.
Snorkel Shifts From Labeling Software to Complete AI Datasets
Snorkel began as a provider of software designed to automate data labeling but shifted last year toward a data-as-a-service model. In its Series E announcement, the company said it now works with frontier AI labs, enterprises and other organizations on datasets, benchmarks and evaluation environments.
Rather than operating primarily as a marketplace that connects AI companies with human contractors, Snorkel combines software, AI-generated synthetic data and subject-matter experts. Its products include completed training datasets and reinforcement learning environments that allow AI models and agents to practice tasks and receive measurable feedback.
The company’s revenue growth reflects increased spending by AI developers on specialized training and evaluation data. Snorkel says its approach focuses on creating data for complex domains where existing datasets may not provide enough coverage.
AI Data Companies Report Rapid Revenue Growth
Other companies supplying data and human expertise to AI developers have also reported large annualized revenue figures. Mercor has reached $2 billion in gross annualized revenue, Handshake passed $1 billion earlier this year, and Micro1 has grown to a $500 million gross run rate, according to TechCrunch.
Those figures are not directly comparable with Snorkel’s reported revenue. Human-expert marketplaces can pay roughly 60% to 70% of their top-line income to the specialists completing work, leaving their net revenue substantially below the headline gross figures.
Snorkel says its accounting differs because it sells finished datasets and reinforcement learning environments rather than human labor itself. Payments to the experts who help create those products are recorded as cost of goods sold rather than deducted from a gross revenue figure.
Co-founder and CEO Alex Ratner and his team began developing Snorkel as a research project at Stanford before the company launched commercially in 2019. Its latest funding will support its work on specialized data and environments for advanced AI systems.
Featured image credits: Wikimedia Commons
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