Snorkel AI
Expert data development and specialized agents for frontier AI models
Enterprise·Technical
Key strengths
Expert-curated datasets for frontier AIResearch-led data and environment developmentCalibrated expert review with gold-set training and bias scoringRubrics and programmatic checks with fine-tuned evaluator modelsFull adjudication and provenance audit trailsOpen benchmarks and leaderboards across multiple domainsSpecialized agents grounded in expert data
Enterprise pricing
Redwood City, USA
Founded 2019
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Documentation & Integration Notes
Snorkel AI's offerings are oriented around three core technical pillars:
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Training Data Production
- Expert-curated datasets tailored for frontier AI use cases
- Calibrated annotation pipelines with gold-set training and bias scoring for annotators
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Evaluation Systems
- Rubric-based and programmatic quality checks
- Fine-tuned evaluator models for automated, scalable assessment
- Full adjudication workflows with end-to-end provenance audit trails
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Benchmarks & Environments
- Open benchmarks and leaderboards spanning multiple domains
- Specialized agent environments grounded in expert-curated data
Teams integrating Snorkel AI into their ML pipelines should expect a research-led, process-driven engagement model focused on data quality, evaluator calibration, and auditability. Provenance audit trails support downstream compliance and reproducibility workflows.
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