agent quality infrastructure

Know when your
agents regress

CohortLens runs the same scenario against your AI agents repeatedly, across versions, and tells you exactly when quality drops. Baselines, not vibes.

$ cohortlens run --suite onboarding --cohort v2.4
Running 12 scenarios across 3 cohort groups...

PASS email_delivery .............. 12/12 consistent
PASS task_creation ............... 12/12 consistent
FAIL landing_page_quality ........ 9/12 regression detected
PASS mission_doc_completeness .... 12/12 consistent

Baseline drift: landing_page_quality dropped 25% vs v2.3
Report saved → cohortlens.app/runs/2026-05-07
01

Cohort-Based Baselines

Run identical scenarios across agent versions. Compare outputs structurally, not just semantically. Detect drift before it reaches production.

02

Regression Detection

Statistical comparison across runs. Know if a quality drop is noise or a real regression. Confidence intervals, not gut feelings.

03

Multi-Step Execution Traces

Evaluate entire agent workflows, not just single outputs. Did it complete all phases? In the right order? With the right artifacts?

04

Automated Scoring

Define quality dimensions that matter: completeness, correctness, consistency, latency. Score every run against your baseline automatically.

Your agents are only as good
as your last baseline.

Ship agent updates with confidence. CohortLens is the quality infrastructure layer between your AI and your users.