.png)
1 month ago
4
Our no-config AI makes in-browser testing simple enough for hobbyists, yet powerful enough for enterprise QA
Fully Managed Browsers w/ No Setup
Fully Managed Testing
From Push to Browser Tests
Connect your GitHub repo and we handle the rest - cloning, building, remote access, and browser testing. All automated.
One-click integration with your repository
We clone your repo and run your build command
Secure tunnel created to your running application
AI agents test your app in real browsers
GitHub Integration Active
Monitoring all PRs • Auto-testing enabled
Everything Managed For You
No DevOps expertise required. DebuggAI handles repository access, dependency installation, build processes, secure tunneling, and browser testing - all through a simple GitHub App installation.
Zero Infrastructure Setup
No servers, containers, or complex configurations. We handle everything from repo cloning to browser orchestration.
GitHub-Native Experience
Install once, forget it. Every PR automatically triggers testing with results posted as comments.
Secure Remote Management
Encrypted tunnels, isolated environments, and temporary access ensure your code stays safe.
AI-Powered Understanding
We Map Your Entire Application
Our AI explores your app to build a comprehensive knowledge graph - understanding every page, interaction, and user flow to run the right tests at the right time.
See It In Action
See Real Results For Every Commit
DebuggAI comments directly on your pull requests with test results, videos, and actionable insights.
Automatic Detection
DebuggAI automatically detects when you open a PR and starts testing immediately.
Inline Results
Test results appear directly in your PR comments - no need to check external dashboards.
Comprehensive Coverage
Every test includes detailed purpose, status, and direct links to debugging information.
github.com/debugg-ai/react-web-app/pull/29
qosha1 wants to merge 1 commit into main from test-yaml
debugg-ai
bot
commented 2 hours ago
🧪 E2E Test Results
📝 Commit: 97e040a5 (PR #29)
AI Test Suites
Make Every Commit A Good One
Debugg AI analyzes your code diffs on every commit to create and run targeted end-to-end tests, ensuring your changes are solid before they're merged.
Commit Analysis: `feat: improve signup`
Status: Analyzing diff...
Generated Test Plan
Validating new form logic...
Test: New user signup
Source: commit 32e94db
Result: Passed
All assertions passed for new signup flow.
Tired of hassling with Playwright & Selenium?
Join the developers saving hours of wasted effort by catching regressions in auth, forms, checkout-like flows before they get deployed.
Why Teams Choose DebuggAI
Ship Code That Actually Works
Stop hoping your code works. Start knowing it does.
Confidence Before Merge
Test actual user flows, not just code structure. PR browser testing lets you catch issues before users do.
Fewer production bugs
Faster Reviews
Reviewers trust the green checkmark. No more manual testing delays.
Faster PR approvals
Simple Learning Curve
Add our GitHub app and workflow file. No frustrating browser config.
2-minute setup, consistent value
Pricing
Start Testing for Free
No credit card. No setup fees. Just better code.
Free
Perfect for open source
Free
- Public repos
- 100 tests/mo
- PR comments
- Community support
MOST POPULAR
Pro
For professional developers
$20/month
- Private repos
- Unlimited tests
- Priority support
- Advanced analytics
Team
For growing teams
Custom
- Everything in Pro
- Multiple users
- SSO/SAML
- Dedicated support
- Custom integrations
PR Testing Resources
Learn best practices for PR-based testing, browser automation, and shipping with confidence.
Causal Debugging: Building a Code Debugging AI That Can Prove Its Fixes
A practical, technical blueprint for a verifiable AI debugger—deterministic replay, dynamic slicing, property-based tests, and symbolic checks—enabling an AI to propose and prove safe, production-ready patches.
Observability for Code Debugging AI: Traces, Prompt Versioning, and Guardrails to Prevent Silent Regressions
How to instrument code debugging AI with end-to-end traces, prompt/version control, offline evals, and safety guardrails—so hallucinated fixes don’t ship and developer trust doesn’t erode.
On-Device vs Cloud: Designing Code Debugging AI That Respects Secrets and Scales
A practical guide to architecting code debugging AI for IDEs and CI: privacy threat models, latency/cost trade-offs, local LLM stacks, data minimization, and reference pipelines that protect repos and speed root-cause analysis.
Ready to Stop Ignoring UI Tests?
Join the developers who visually test every PR automatically.
No credit card. No complex setup. Just easy end-to-end testing.
Setup takes 2 minutes.
