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Two Ways to Integrate

QA.tech offers two integration modes for CI/CD:
FeatureAPI-Driven TestingAI Exploratory Testing
How it worksYou define test plans, trigger via APIAI analyzes PR, creates & runs tests
CI/CD SupportAny system (GitLab, GitHub, Bitbucket, Azure DevOps, CircleCI, Jenkins)GitHub App and GitLab integration
Test SelectionYou choose which test plan to runAI selects relevant tests automatically
Test CreationYou create tests in QA.tech UI or via APIAI creates tests for new functionality
Best ForRegression testing, scheduled runs, deployment gatesExploratory testing of new features
Which mode should you use? - API-driven: Use for regression testing, scheduled test runs, or when you want full control over which tests run - AI exploratory: Use GitHub App or GitLab integration when you want AI to discover and test new functionality automatically

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API-Driven Testing

Works with any CI/CD system that can make HTTP requests. You create test plans in QA.tech, then trigger them programmatically from your pipeline using a simple REST API call. This approach gives you full control over which tests run, when they run, and which environments to test - perfect for regression testing, deployment gates, and scheduled test suites.

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How It Works

  1. Create test plans in QA.tech - organize your test cases into logical groups
  2. Trigger via REST API from your CI/CD pipeline
  3. Test runs execute against your configured environments
  4. Results available in QA.tech dashboard and via API

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What You Can Do

  • Test preview/staging environments - Override application URLs dynamically when testing Vercel, Netlify, or custom preview deployments. See Preview Environments.
  • Override device configurations - Test with different device presets per-run via API, allowing you to test mobile, tablet, and desktop configurations without creating separate test plans. See Start Run API for devicePresetShortId parameter details.
  • Block deployments until tests pass - Wait for test results before proceeding with your pipeline. The GitHub Action has built-in blocking support; other platforms can poll the Run Status API to wait for completion.
  • Schedule recurring test runs - Set up nightly regression suites or periodic smoke tests using your CI/CD system’s cron functionality.
  • Custom Slack notifications - Send test results to specific Slack channels per-run, separate from your project’s default channel. See Notifications.
  • Run specific test plans - Target regression suites, smoke tests, or full test suites by specifying the test plan short ID.
  • Custom post-run automation - Use the Run Status API to trigger webhooks, update status pages, or send custom alerts when runs complete.

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Get Started

QA.tech works with any CI/CD platform that can make HTTP requests. We provide detailed guides for:
  • GitHub Actions - Official GitHub Action with built-in blocking mode
  • GitLab CI - GitLab CI/CD pipeline integration via API
Other platforms (Bitbucket Pipelines, Azure DevOps, CircleCI, Jenkins, and more) can integrate using the REST API directly. See the Start Run API Reference for complete API documentation and examples.

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AI Exploratory Testing (GitHub and GitLab)

QA.tech exploratory review integrations automatically analyze pull/merge requests, identify user-facing changes, and create tests for new functionality. They run those tests against your preview deployment context and post results back to the request discussion. This helps catch issues before merge without requiring you to manually write tests for every feature.

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How It Works

  1. Analyzes request changes - Examines code diff and identifies user-facing changes
  2. Selects relevant tests - Finds existing tests that apply to the changes
  3. Creates missing tests - Generates tests for untested functionality
  4. Runs tests - Executes against PR preview deployment
  5. Posts review - Comments on the request with test results and approval/rejection

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Requirements

  • GitHub App or GitLab integration connected to your repository
  • Preview deployment context available (native deployment signals or manual @qa.tech comment with preview URL)
  • Repository selected in QA.tech integration settings
AI exploratory testing is available through:For other platforms, use API-driven testing.