QA Copilot
Fix Flaky Tests Automatically with AI
Detect, explain, and patch nondeterministic tests — no manual triage. 79% of developers see flakiness as a serious problem; QA Copilot turns retries and guesswork into observable, auto-remediated fixes.
No credit card required.
Trusted by QA teams at
Key advantages
What teams get with Flaky Tests
Self-healing tests
Generates resilient locators, right-sizes waits, and suggests assertion relaxations — automatically.
Deterministic execution
AI Vision and intent detection replace sleeps; fewer false negatives in your CI pipeline.
Evidence packs
Auto-attach logs, screenshots, and session videos — solving the hardest part: reproducing context.
The Problem
The Flakiness Reality
Industry research shows how widespread and costly flakiness has become — and why automation for detection, diagnosis, and verified fixes is essential.
79% report serious impact
Flakiness is a moderate-to-serious problem for most teams; 58% face flakes monthly and 40% deal with them weekly or daily.
Top causes: 26% / 22% / 17%
Concurrency, async waits, and overly strict assertions are the main culprits behind flaky runs.
34% start in production code
Nearly a third of concurrency flakes stem from app code — not tests — so fixes demand insight beyond the test harness.
75% disable instead of fix
Teams often turn off time-based flakes, letting instability linger and masking regressions.
86% add more waits
Adding waits is the knee-jerk response — 46% for concurrency issues and 86% for async ones — creating tech debt and hiding real failures.
#1 pain: reproducing context
Teams struggle to rebuild failing scenarios; QA Copilot auto-captures logs, screenshots, and session replays so engineers can fix with confidence.
How It Works
How It Works
Train once under supervision. Then QA Copilot keeps your test intent green — even when the UI shifts — by silently self-healing at runtime.
Train on a test case
Provide the step intent from your existing test case — targets, actions, expected outcome. No point-and-record; Copilot learns from explicit instructions.
Assign to plans
Add the trained case(s) to your test plan; Copilot executes them in CI automatically.
Intent over selectors
If a button, label, color, or DOM path changes, Copilot uses visual and semantic cues to select the right target and honor the step.
Silent self-healing
No diagnostics UI and no patch proposals — Copilot adjusts selectors, waits, and assertions at runtime to keep tests stable.
Direct fix execution
Fixes are applied automatically during execution; engineers don't need to intervene.
Full-session recording
Every run is video-recorded for audit or later review.
Compare
Manual Triage vs QA Copilot
See how QA Copilot replaces manual flaky test triage across every dimension.
Setup
Manual: Engineers re-interpret each test's steps and environment whenever it fails.
QA Copilot: Train once with manual instructions (no recording needed); afterward it runs autonomously in CI or on-demand.
When a test flakes
Manual: Teams comb through logs, retries, and screenshots to understand what broke.
QA Copilot: Executes the trained intent; if UI drift or timing issues appear, it corrects them silently.
UI changes
Manual: Updated selectors, colors, or layout changes trigger breakage and manual locator fixes.
QA Copilot: Uses visual + semantic intent matching to choose the right element even when selectors shift.
Timing & waits
Manual: Sleep/retry adjustments are guesswork and often hide real failures.
QA Copilot: Adjusts waits and assertions at runtime to honor the intended outcome.
Evidence trail
Manual: Logs and captures are ad hoc; missing context slows root-cause work.
QA Copilot: Records every session and stores artifacts automatically.
Code changes required
Manual: Engineers create PRs to patch selectors or waits again and again.
QA Copilot: Applies fixes during execution — no code changes land in the repo.
Coverage continuity
Manual: Disabling flaky tests is common, eroding coverage.
QA Copilot: Keeps the original test intent validated, so quality signals remain intact.
Engineer time cost
Manual: Hours or days per recurrence across QA and dev teams.
QA Copilot: Once trained, it runs unattended; humans focus on real product defects.
FAQ
Answers teams look for
What are flaky tests?
Flaky tests are tests that pass and fail intermittently without any code changes. Common causes include concurrency issues, async timing problems, and overly strict assertions. QA Copilot detects and fixes these automatically.
How does QA Copilot fix flaky tests?
QA Copilot uses AI vision and intent detection to understand what each test step is trying to do. When UI elements shift or timing changes, it adjusts selectors, waits, and assertions at runtime — keeping tests green without manual intervention.
Do I need to modify my existing tests?
No. You train QA Copilot on your existing test cases by providing step intents. After that, it runs autonomously in CI and self-heals when it detects flakiness.
What evidence does QA Copilot capture?
Every test run is fully recorded with video, screenshots, logs, and session replays. This solves the #1 pain point teams report: reproducing the context of a flaky failure.
Is there a free trial?
Yes. You can start a free trial and evaluate QA Copilot's flaky test detection and self-healing in your own workspace before upgrading.
