Anthromind

Anthromind helps AI teams get the human data their models need.

Every AI model is trained and tested on data made by people, and the quality of that data sets the ceiling on how good the model can be. We produce that data using people who genuinely know the subject, in areas like law, finance, coding and STEM, rather than general crowd workers.

What we do:

Evaluation. We measure how well your model actually performs, using benchmarks built for your specific use case instead of generic ones. That includes testing RAG systems for hallucinations and weak context.

RLHF and preference data. We collect expert judgments on which model output is better, so your model learns to prefer the right answers. This holds up on hard problems where a non-specialist would only be guessing.

Post-training datasets. We build custom datasets that improve accuracy, add domain expertise, or give a model a consistent tone and style.

Reasoning data. We create and evaluate step-by-step chain-of-thought data, including problem breakdown, backtracking and answer verification.

Who we work with:

• Foundation model labs building frontier models
• Enterprise teams moving AI from pilot to production
• Academic researchers who need rigorous human evaluation