Snorkel
Generate training data with weak supervision quickly.
- Status
- Generally available
- Last checked
- Aging · Sep 3, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Snorkel is a system for rapidly creating labeled training datasets using weak supervision techniques. It allows users to label data programmatically, making it easier and faster to generate high-quality training sets without manual labeling.
Snorkel stands out as an efficient tool for automating the creation of labeled datasets, reducing the time and effort required to prepare training data for machine learning models.
When it fits — and when it doesn’t
A good fit for
Teams needing to quickly generate training datasets without extensive manual effort
Projects with limited labeled data but a need for rapid model development
Look elsewhere if
Scenarios requiring real-time labeling or interaction with live data streams
Applications where the quality of manually curated labels is critical and cannot be compromised by automated methods
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited documentation for advanced use cases
Complex scenarios and best practices are not well-documented in official guides
- 02
Performance issues with large datasets
Processing time increases exponentially with the size of input data, leading to long wait times for results
What it does well
Weak supervision for labeling data programmatically
Automated generation of training datasets
Integration with machine learning pipelines
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up Snorkel
Setup steps, common gotchas and what to check after 30 days.