Staging metrics, finally understood

Your staging environment
is lying to you. We fix that.

Stagewise uses AI-powered cohort analysis to compare every deploy against your baseline. Regressions surface before they reach production. Teams ship with confidence, not crossed fingers.

40%
reduction in unplanned work
3x
faster regression detection
0
config required to start
How it works

Cohort analysis for every deploy that hits staging

■

Automatic Baseline Cohorts

Every deploy creates a metrics snapshot. Stagewise builds a rolling baseline from your last N deploys, so anomalies are measured against your team's actual patterns.

▲

AI Regression Alerts

Not just thresholds. The AI understands which metric spikes matter and which are noise, correlating performance changes to specific code paths and services.

●

Team-Level Patterns

See which teams ship cleanly and which introduce repeated staging regressions. Turn observability data into productivity insights for engineering leadership.

♦

CI/CD Native

Hooks into GitHub Actions, GitLab CI, and staging platforms like Render and Vercel. Telemetry collection starts the moment your preview deploys.

The view

Compare. Detect. Ship clean.

deploy #41
P95: 142ms
deploy #42
P95: 189ms
deploy #43
P95: 347ms
Regression detected: P95 latency on /api/checkout is 2.4x the 5-deploy cohort baseline. Correlated with commit a3f9e2b (new middleware added by payments-team).

Production fires start in staging.
Now you can see them forming.

Stagewise turns your staging environment from a checkbox into a signal. Every deploy, every metric, every team, understood.