Snorkel AI provides Data Labeling & Annotation services for frontier AI development. The company builds expert-curated training datasets, evaluation systems, preference labels, and executable environments that AI teams use to train and assess models and agents.

Key Capabilities

Custom data development: Designs specialized datasets, expert demonstrations, reasoning traces, preference rankings, and reviewer guidance for specific model failure modes.
Evaluation systems: Produces rubrics, deterministic graders, benchmarks, and evaluation slices to measure model and agent performance.
Runnable agent environments: Creates simulated browser, graphical user interface (GUI), command-line interface (CLI), repository, and tool-use environments for training and evaluating agents on multi-step tasks.
Expert review and provenance: Uses calibrated expert reviewers, multi-stage adjudication, and audit trails to maintain data quality and traceability.
Specialized agents: Develops custom AI agents grounded in expert data and evaluated against workflow-specific success criteria.

Product and Solution Areas

Snorkel Data Series: Curriculum-structured datasets with built-in rubrics, difficulty tiers, reviewer guidance, and evaluation slices.
Custom Data Development: Bespoke datasets, evaluations, and benchmark expansions for specialized AI tasks.
Specialized Agents: Custom agents designed for high-consequence workflows and assessed in task-specific environments.
Research Benchmarks: Public benchmarks and leaderboards for coding, computer-use, legal, scientific, and other agent tasks.

Audience & Use Cases

Audience: Frontier AI labs, AI research teams, enterprise AI developers, and AI-safety teams.
Use Case: Supports the development of coding agents, computer-use agents, research assistants, domain-specific AI systems, and models that require expert-created training and evaluation data.

Snorkel

What is Snorkel?

Categories & Use Cases