Replay QA Overview

Replay QA is an autonomous app testing tool built on Replay's time-travel debugging engine. Point it at a web app and it explores the application, discovers user journeys, writes Playwright tests, executes them while capturing full runtime recordings, and uncovers bugs — delivering a detailed root cause analysis and suggested fix for every issue it finds.

There are three ways to use Replay QA depending on your workflow.

A few tips for best results:

1. React-based apps work best. Replay QA has deep React support — component tree inspection, render tracing, and effect analysis — that significantly improves the depth of bug reports for React apps.
2. Publish your app with source maps. When source maps are available, Replay QA traces failures back to your original source code rather than compiled output, producing root cause analyses and suggested fixes that reference the right files and line numbers. Learn more

Stand-alone

Give Replay QA a URL. It takes it from there.

Replay QA autonomously navigates your application, discovers user journeys, and generates Playwright tests. It then executes those tests using Replay Browser — capturing a full runtime recording of every interaction. When it uncovers a bug or unexpected behavior, it time-travels the recording to trace the failure back to its root cause, and delivers a detailed analysis with a suggested fix.

This requires no existing test suite, no configuration, and no manual reproduction steps.

Launch Replay QA

Ask your coding agent

Give your coding agent the prompt below and it will use the Replay QA REST API to create a new project for your app, poll for status as Replay QA explores and tests the application, and ingest the resulting bug reports — each packaged with the runtime context and root cause detail your agent needs to go straight to a fix. It keeps looping until no open bugs remain.

Set up a continuous QA loop for the app we're building using Replay QA (https://loop-qa.replay.io).

Drive everything through the REST API at https://loop-qa.replay.io/api/v1 — read the OpenAPI spec at /api/v1/openapi.json first; it documents the full workflow. Authenticate with my API token ("Authorization: Bearer lqa_..."), asking me for it if needed.

Your job:
1. Create a QA project for the running app — give it the target_url and a short note on the key flows. If the app is only reachable from this machine (e.g. http://localhost:3000), enable the reverse proxy and follow the spec's setup steps.
2. Let QA run — poll the project status and don't kick off explorations or test runs yourself; QA drives those.
3. For each open bug, read its full root-caused report and apply the fix directly in the codebase, then mark it fixed via the API.
4. Keep looping until no open bugs remain.

Integrated into your CI pipeline

Install our GitHub bot (CI Agent) and configure your test suite to record with Replay. From that point, every test run in CI produces a Replay runtime recording. When a test fails, the CI Agent time-travels the recording, and posts a comment directly on the pull request with:

• A plain-language root cause explanation
• A trace showing the execution chain from symptom to cause
• A suggested code fix with file and line references

No reproduction steps. No log archaeology. The evidence is already in the recording.

See GitHub Actions setup to configure Replay in your workflow, and PR Comments to install the GitHub bot.

How Replay's time-travel engine works

All three modes share the same foundation: deterministic browser recordings captured by Replay Browser. Unlike video or snapshots, a Replay recording captures the full browser runtime — every DOM change, every network request, every line of JavaScript execution.

That means any point in a test run can be inspected retroactively: add console logs, evaluate expressions, examine call stacks, trace render behavior — all without re-running the test.

Learn more about how time-travel debugging works →

FAQ