Green doesn't mean safe. Red doesn't mean broken. 84% of failures are flaky. Zerocheck gives you a calibrated confidence score per PR that accounts for what changed, what was tested, and how reliable the results are.
“At Google, we found that 84% of pass-to-fail transitions are caused by flaky tests, not real bugs.”
Google Testing Blogsource
“Test failures are ignored, builds are rerun blindly, and every green pipeline is suspect.”
Dmytro Huz, DEV Communitysource
84% of CI failures are flaky, not real bugs
No testing tool produces a calibrated per-PR confidence score
Binary pass/fail gates are overridden 10-20% of the time at most companies
Every testing tool outputs binary pass/fail. But green doesn't mean 'safe to ship' when irrelevant tests passed. And red doesn't mean 'broken' when 84% of failures are flaky noise.
Testim and Mabl have element-level confidence for self-healing, but not PR-level confidence. Datadog monitors report status, not risk per change.
The unmet job: given this specific PR, what is the probability it breaks a critical user flow? Nobody answers this question today.
Developer pushes PR. CI runs 200 tests. 6 fail. Are they real? Developer investigates for 45 minutes. 5 are known flakes, 1 is a real issue in an unrelated module. Developer fixes, re-runs, waits again. Total time wasted: 2 hours. Confidence in the merge: uncertain.
Same PR. Zerocheck analyzes the diff, runs targeted tests, and reports: 'Confidence: 94%. 4 tests ran (all relevant to checkout changes). 1 tier-3 warning on settings page (nightly). 0 flakes.' Developer merges in 5 minutes with evidence attached.
PR diff analyzed to identify affected user flows
Tests run with flake-vs-real classification per failure
Confidence score accounts for test relevance, flake history, and business tier
PR comment shows score + evidence, not just red/green
Per-PR confidence scores, not binary pass/fail. Know exactly how safe each change is to ship.
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