Headquarters
Redwood City, CAFounded
2019CEO / Founder
Alex RatnerEmployees
51-200Funding
Series D — $235MProducts
1 product listedAvg. AI Score
7.8/10Website
snorkel.aiProfile updated
Snorkel AI is a data development platform founded in 2019 in Redwood City, California by Alex Ratner and fellow researchers spun out of the Stanford AI Lab. Its programmatic labeling technology enables enterprises to build and curate high-quality training datasets for LLMs and specialized AI models.
Snorkel serves Fortune 500 enterprises and government agencies, including financial services, healthcare, and defense customers. Its Snorkel Flow platform combines programmatic labeling with expert human feedback to accelerate model development.
Snorkel has raised approximately $235 million, including a Series D led by Addition and Greylock, with participation from Lightspeed, Walden, GV, and In-Q-Tel. The company was most recently valued at approximately $1 billion.
Dated, source-cited figures. Estimates are marked.
All products by Snorkel AI reviewed by our AI panel of experts.
Six independent reviewer personalities assessed Snorkel AI's product on their own terms. They landed within 0.6 points of each other, an unusually strong consensus.
Averaged across 1 reviewed product in our catalog. Scores are out of 10.
Who Snorkel AI competes with, and how they differ.
Scale is the larger, more diversified data-labeling incumbent for frontier labs and government; after Meta took a ~49% stake and hired away CEO Alexandr Wang in mid-2025, Scale leaned further into large-lab RLHF contracts and cut 14% of staff, while Snorkel stays independent with a smaller, enterprise-focused programmatic-labeling and evaluation platform.
1 product reviewed on TopReviewedSurge AI is a pure human-data and RLHF shop serving OpenAI, Anthropic, Google, and Meta directly, with no self-serve labeling software product — it competes with Snorkel's newer "expert data-as-a-service" line rather than Snorkel's core programmatic-labeling tooling.
Labelbox is a workflow-based annotation platform built around human-in-the-loop labeling (image, video, text, document) plus active learning, whereas Snorkel differentiates on programmatic labeling functions and weak supervision that reduce manual annotation volume.
1 product reviewed on TopReviewedKey milestones in Snorkel AI's history, with sources.
Lays off 13% of workforce in pivot to data-as-a-service
Snorkel AI cut 31 of its 240 employees, hitting the software engineering team hardest while sparing most AI-focused roles, as it shifted toward a data-as-a-service business and deprioritized legacy areas.
businessinsider.comAccenture Ventures makes strategic investment
Accenture made a strategic investment through Accenture Ventures to help enterprises, particularly in financial services, curate high-quality datasets for training and evaluating AI models with Snorkel.
newsroom.accenture.comSeries D — $100M at $1.3B valuation
Snorkel AI raised a $100 million Series D led by Addition, with Prosperity 7 Ventures, Greylock, Lightspeed, BNY, and QBE Ventures participating, valuing the company at $1.3 billion — a 30% step-up from 2021.
businesswire.comSeries C — $85M at $1B valuation
Snorkel AI raised an $85 million Series C led by BlackRock and Addition, reaching unicorn status at a $1 billion valuation.
snorkel.aiSeries B — $35M led by Lightspeed
Snorkel AI raised a $35 million Series B led by Lightspeed Venture Partners, with Greylock, GV, In-Q-Tel, Nepenthe Capital, Walden, and BlackRock participating; total funding reached $50M. The round also introduced Application Studio.
techcrunch.comEmerges from stealth with Snorkel Flow
Snorkel AI publicly launched its programmatic data-labeling platform, having raised $15M to date across seed and Series A.
snorkel.aiSeries A — $12M
Snorkel AI raised a $12 million Series A, bringing early funding to $15M.
forbes.comSeed round — $3M
Snorkel AI closed a $3 million seed round.
forbes.comFounded as a Stanford AI Lab spinout
Snorkel AI was founded by Alex Ratner, Christopher Ré, Braden Hancock, Henry Ehrenberg, and Paroma Varma, commercializing four years of weak-supervision research at the Stanford AI Lab.
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