Data labeling for enterprise AI and coding.

Annotation pipelines for SFT, DPO, preference pairs, and evals. Domain-vetted raters, calibrated rubrics, adjudicated disagreements.

Enterprise AI

Support automation, RAG retrieval quality, agent trajectories, document understanding, and voice. Specs written against your eval criteria.

Coding data

Multi-turn PR review, repository-scale agent traces, bug repair, refactor reasoning, and test-grounded completions. Raters are working engineers.

  1. 01/04

    Rubric and pilot

    A 50–200 example pilot to tune the spec. We rewrite the rubric until inter-annotator agreement clears your threshold, then scale.

  2. 02/04

    Domain-vetted workforce

    Engineers review coding tasks. Subject-matter specialists review enterprise tasks. Raters are tested against gold sets, retested weekly, and rotated on persistent disagreement.

  3. 03/04

    Adjudication

    Triple-review on a sampled fraction, continuous IAA tracking, and drift detection across batches. Disagreements are resolved by a senior reviewer.

  4. 04/04

    Delivery

    Streamed via S3 or webhook, deduplicated and schema-validated, provenance-tagged at the row level. SFT, DPO, preference pairs, or eval format.

Y Combinator
Hugging Face
Google
Harvard Medical

Send us a spec.

An annotation criterion, a data sample, or a problem statement. We respond within a day.

Email the founders

Best for longer threads or attaching files.

[email protected]