Data labeling & annotation · Snorkel AI, Inc.
Snorkel AI
Programmatic-labeling platform (Snorkel Flow) that generates training labels from heuristic rules and weak supervision instead of manual annotation.
Snorkel AI's core product, Snorkel Flow, takes a different approach from manual annotation tools in this category: instead of humans labeling each example, users write "labeling functions" — heuristic rules, keyword patterns, existing model outputs or crowdsourced signals — and Snorkel's weak-supervision algorithms combine these noisy sources into a single probabilistic label per example across a large dataset. This programmatic approach can label far faster and cheaper than manual annotation for suitable use cases, and supports active-learning loops to target where human review adds the most value. More recently the company has also moved into expert data-development services for frontier AI labs — custom evaluation datasets, rubrics and specialized agent environments — sold separately from the Snorkel Flow platform. It deploys as a managed cloud service or in a customer's own VPC for enterprise and government customers.
At a glance
| Vendor | Snorkel AI, Inc. |
|---|---|
| Pricing model | Quote only |
| Free tier | — |
| Deployment | Cloud, Self-hosted |
| Open source | No |
| Best for | Teams that want to generate training labels programmatically at scale rather than annotate manually example by example. |
Pricing
No public pricing found; quoted per deployment, contact sales.
Pricing has not been verified yet — see the vendor's site.
Features
- Programmatic labeling via user-defined labeling functions
- Weak-supervision algorithms combining multiple noisy label sources
- Active learning to prioritize human review effort
- VPC/on-prem deployment for enterprise and government customers
- Data-quality and drift monitoring on labeled datasets
- Expert data-development services for frontier LLM/agent evaluation
- Integration with existing model outputs as label sources
Integrations
Profile last reviewed September 21, 2026