Snorkel AI
Programmatic data development and agentic data factory for enterprise AI.
About
Snorkel AI is an enterprise data development platform born from Stanford's programmatic labeling research. It lets teams create training data with labeling functions and weak supervision instead of pure manual annotation, and it has shifted toward a data-as-a-service model with an agentic data factory for building expert datasets.
On September 22, 2026 it raised a $350 million Series E led by Insight Partners and S32 at a $3.5 billion valuation, with annualized revenue run-rate reported above $350 million.
The platform is enterprise-focused with enterprise pricing, and programmatic labeling has a real learning curve for teams new to the paradigm. Funding and revenue figures are vendor-reported.
What it can do
- Programmatic data labeling with labeling functions
- Weak supervision to cut manual annotation
- Agentic data factory for expert datasets
- Model development and evaluation workflows
Setup
Request a demo at snorkel.ai; enterprise sales-led onboarding.
Prerequisites
Enterprise AI project with large data-labeling needs and budget for a data platform.
Use cases
Works with
Trust score — 9/10
Scored 9/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 72; Trending score 90/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.