Debugg AI

Overview

Debugg AI is an automated end-to-end (E2E) browser testing platform designed to integrate seamlessly with your GitHub workflow. It eliminates the need for manual browser configuration, complex DevOps setups, or custom test scripting by providing zero-config, AI-driven in-browser tests for every pull request (PR). Whether you are a solo hobbyist developer or part of a large enterprise QA team, Debugg AI enables you to ship reliable code faster by catching visual and functional regressions before they reach production.

By leveraging AI agents that explore and understand your entire application, Debugg AI dynamically maps UI elements, user flows, and interactions. This deep understanding allows the platform to run targeted tests whenever you push changes, ensuring comprehensive coverage without the need to maintain massive static test suites.

Key Features

Zero-Config Setup

• Instant GitHub Integration: Connect your repo via a one-click installation of Debugg AI’s GitHub App.
• No DevOps Expertise Required: Debugg AI handles repository cloning, build processes, dependency installations, browser orchestration, and secure tunneling.
• Works With Any Stack: No matter your programming language or front-end framework, Debugg AI adapts automatically.

Fully Automated Testing Workflow

1. Push Your Code: Open a pull request in GitHub.
2. Automatic Test Trigger: Debugg AI detects the PR and starts testing immediately.
3. Cloning & Building: Your repo is cloned, build commands executed, and the application is deployed to an isolated environment.
4. Secure Access: Encrypted tunnels provide the test agents with controlled remote access.
5. Browser Testing: AI agents run tests across real browsers, simulating actual user behavior.

AI-Powered Application Understanding

• Knowledge Graph Mapping: Debugg AI explores your app to understand every page, interaction, and path.
• Targeted Test Generation: Tests are dynamically created based on code changes, ensuring relevant and efficient coverage without redundancy.

In-PR Reporting

• Inline PR Comments: Test results are posted directly in your pull request so reviewers see pass/fail statuses without leaving GitHub.
• Detailed Artifacts: Each test includes a purpose, status, duration, and direct links to video recordings and debugging info.

Security-Focused Infrastructure

• Isolated Environments: Each test run happens in a sandbox to prevent unwanted code exposure.
• Encrypted Tunnels: Secure communication channels protect your code during remote testing.
• Temporary Access: No lingering connections—reducing long-term security risks.

Tiered Pricing

• Free Plan: Public repos, 100 tests/mo, community support.
• Pro Plan ($20/mo): Private repos, 1,000 tests/mo, priority support, advanced analytics.
• Grow Plan ($40/mo): 5,000 tests/mo, team management, add-ons, priority support.
• Enterprise: Unlimited tests, SSO/SAML, dedicated support, custom integrations.

Use Cases

1. Continuous UI Regression Testing

Teams can maintain quality across fast-moving codebases, catching visual and interactive discrepancies as soon as they are introduced.

2. Accelerated Code Reviews

Debugg AI’s in-PR test results provide immediate confidence for reviewers, enabling faster merges and fewer review cycles.

3. Cross-Browser Compatibility Validation

AI agents simulate real user flows across multiple browsers without needing local setup or browser-specific scripts.

4. Open Source Maintenance

Maintainers of popular projects can ensure consistent behavior as contributions roll in without spending hours on manual verification.

5. Startup Deployment Confidence

For small dev teams, Debugg AI’s automation replaces time-consuming manual E2E testing, freeing resources for core development.

FAQ

How does Debugg AI know what to test in my PR? Debugg AI analyzes code diffs and applies its knowledge graph to generate relevant test cases targeting affected user flows.

Do I need to configure anything? No. Setup involves installing the GitHub App and adding a workflow file—Debugg AI handles the rest.

What happens after I open a pull request? Debugg AI automatically clones your repo, runs the build, launches your app in a managed browser, and tests it before posting results inline.

What tech stacks are supported? Any stack. Debugg AI works with all major frameworks and languages without additional configuration.

Is my code secure? Yes. Testing occurs in isolated environments via encrypted tunnels with temporary access.

Can I try Debugg AI for free? Yes. Public repositories get 100 tests per month with community support at no cost.

---

Debugg AI turns PR-based testing into a seamless, automated part of your development process, helping you ship code with confidence that it will perform flawlessly in production. With rapid setup, AI-driven insights, and direct in-PR reporting, it removes the friction from browser-based E2E testing entirely.