AssayKit runs cohort-based quality baselines against your AI agent outputs. Detect regressions across model swaps, routing changes, and code deploys with a single stable reference point.
Run the same scenarios across agent versions. Measure output consistency, correctness, and completeness as a stable cohort, not isolated tests.
Catch quality regressions from model swaps, prompt changes, or routing updates before they reach production. Automated alerts when scores drop below your threshold.
Full visibility into agent decision paths. Compare how the same scenario resolves across different agent configurations, side by side.
Gate deployments on quality scores. If the baseline drops below threshold, the deploy fails. No more shipping regressions to production.
Write the agent interactions you care about. Multi-turn, tool-using, autonomous flows.
Run your scenarios once to set the reference. This is your quality floor.
On every deploy, routing change, or model swap, run the cohort again. Scores drift? You know immediately.
AssayKit gives your agent team the confidence to ship fast by making quality visible, measurable, and impossible to ignore.