Moon runs the evals your model ships against, tracks the regressions before your users find them, and hands your team the recipe for the next release.
Moon runs your evals on the prompts your users actually send, not just the benchmarks a paper claimed matter.
Every eval gets both. Moon surfaces where the model rater is fooling itself and where the humans disagree.
Every regression comes with the failure mode, the diff, and the smallest change likely to fix it.
Moon is the first eval platform that told us
which regression to fix first.
Drop in the Moon SDK, register your evals, ship every release with the score attached and the recipe queued.
# Score a release against your evals from moon import Evals evals = Evals("support_agent") .register("tone", "grounding", "safety") .run(release="v42") print(evals.summary()) # pass 94.2, regressions 2, recipe attached
Free on the first hundred evals. Bring a prompt, we bring the raters, and the first score lands within an hour.