Blog

Notes on expert data.

Research, methodology and field notes from the team building the expert workforce for AI.

Why frontier models need licensed experts, not crowd raters

As models approach professional-grade performance, the people grading them must be professionals too.

How we quantify agreement between experts — and why raw accuracy isn't enough.

A practical framework for finding failures in legal, clinical and financial AI before your users do.

The playbook we use to take enterprise teams from scoping to a certified eval set in five days.

License lookups, identity checks and domain assessments — how we vet every contributor.

Why paying more per label often lowers the total cost of a high-quality model.

Talk to our team about your evaluation and data needs.