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End-to-end AI data development platform for frontier AI and agentic systems.

Snorkel AI is a data development platform that enables AI teams to design, stress-test, evaluate, and improve the data powering their frontier models. It operationalizes the full AI data loop, from dataset curation and realistic simulations to rubric design and evals. The platform provides end-to-end solutions for advancing AI and agentic systems. It supports programmatic quality control and expert-in-the-loop acceleration, facilitating faster iteration on data and evaluations. Snorkel's platform provides a unified engine to define tasks, execute rubric-guided pipelines, refine models based on failure analysis, and evaluate behavior through realistic simulations, ensuring reproducible results and traces. Snorkel addresses AI stalls by providing a robust data development engine to overcome challenges like shifting targets, edge cases, uneven quality, and one-off evals.
Snorkel AI is a data development platform that enables AI teams to design, stress-test, evaluate, and improve the data powering their frontier models.
Explore all tools that specialize in annotate training data. This domain focus ensures Snorkel AI delivers optimized results for this specific requirement.
Explore all tools that specialize in generate synthetic data. This domain focus ensures Snorkel AI delivers optimized results for this specific requirement.
Explore all tools that specialize in develop ai models. This domain focus ensures Snorkel AI delivers optimized results for this specific requirement.
Explore all tools that specialize in manage data pipelines. This domain focus ensures Snorkel AI delivers optimized results for this specific requirement.
Explore all tools that specialize in data curation. This domain focus ensures Snorkel AI delivers optimized results for this specific requirement.
Automates the creation of training data using labeling functions.
Evaluates the performance of evaluation metrics themselves.
Tools to develop and refine custom evaluation metrics.
Integrates human experts into the data labeling and evaluation process.
Simulates real-world scenarios to stress-test AI models.
Ensures that evaluation results can be consistently reproduced.
Install the Snorkel AI Data Development Platform.
Set up user roles and permissions.
Upload your dataset to the platform.
Define tasks, IO contracts, and scoring rubrics.
Run rubric-guided task and labeling pipelines.
Analyze failures and disagreement to update rubrics.
Target data collection to close coverage gaps.
Evaluate model behavior with coding tasks and realistic simulations.
Publish reproducible results and traces.
All Set
Ready to go
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