Strongest current signal
Package downloads
74.5K/30d
Tracked on PyPI
▲ +53%
Data-centric AI platform for programmatic data labeling and curation
Best current coverage: 74.5K downloads/30d, 14 dependents, and 65 public repos.
Lead signals
Package pull and public code usage both show up clearly for Snorkel AI.
Strongest current signal
74.5K/30d
Tracked on PyPI
14
Known dependents on PyPI
5.9K
Main repository stars
65
Public repositories importing tracked packages
Research Brief
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package pull and existing public code are the clearest current signals for Snorkel AI.
Package pull
74.5K/30d
Tracked package pull on PyPI
Existing public code
65
Public repositories importing tracked packages
Downstream usage
14
Known dependents on PyPI
GitHub attention
5.9K
Main repository stars
Coverage includes npm and PyPI registries, GitHub, public code import detection, distribution surfaces, and recent company news where available. As of April 13, 2026. Methodology
Sustainability and maintenance signals from the primary public repository.
These signals come from public code import detection and tracked hiring posts rather than registry totals alone.
Public repositories and source files importing packages tied to Snorkel AI.
Background and reference details
background, categories, funding, and tools stay collapsed until you need them.
Snorkel AI provides a data-centric AI platform, Snorkel Flow, that enables enterprises to programmatically label, curate, and manage training data. By focusing on improving data quality and quantity, the platform helps organizations accelerate the development and deployment of AI applications. Its significance lies in addressing the critical bottleneck of data preparation, making AI development more efficient and scalable.
Raised $138M total - DAI rank #100 suggests moderate developer adoption relative to funding.
Addition, BlackRock
BlackRock
GV, Greylock
GV, Greylock, In-Q-Tel
2K PyPI
Data-centric AI platform for programmatic data labeling and curation
A data-centric AI platform that helps enterprises programmatically build, adapt, and scale AI applications faster by improving the quality and quantity of training data.
Historical metrics for Snorkel AI
Snorkel AI: PyPI Downloads down 84% (11.5K to 1.8K). GitHub Stars up 0% (5.9K to 5.9K). HuggingFace Downloads up 41% (715 to 1.0K).
| Date | PyPI Downloads | GitHub Stars | HuggingFace Downloads |
|---|---|---|---|
| Mar 15, 2026 | 11.5K | 5.9K | 715 |
| Mar 22, 2026 | 14.1K | 5.9K | 728 |
| Mar 29, 2026 | 21.6K | 5.9K | 748 |
| Apr 5, 2026 | 19.4K | 5.9K | 1.0K |
| Apr 12, 2026 | 11.7K | 5.9K | 1.1K |
| Apr 13, 2026 | 1.8K | 5.9K | 1.0K |