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Webhook debugging tool that captures every delivery, shows why it failed and lets you replay the exact payload after a fix.
Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Agentic QA platform that drives a real browser or live API to verify AI-generated code and hands agents a fixable bug report.
AI API regression-testing solution for streamlined QA and faster releases.
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- ✦Capture every webhook delivery with status and attempts
- ✦Inspect request, response and headers
- ✦Replay and retry exact payloads
- ✦Failure categorization by reason
- ✦Group repeated failures into incidents
- ✦Slack and webhook alerts
- ✦One-command deploy from Docker Compose
- ✦Deploys into your own or a customer's cloud account
- ✦Native managed LLM access (Bedrock/Vertex/Azure AI)
- ✦Managed Postgres, MongoDB and Redis
- ✦Auto-configured IAM, VPC, TLS and load balancing
- ✦Open-source CLI and cloud providers
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦Live browser/API testing rather than mocked assertions
- ✦Auto-generated failure bundles with root-cause hypotheses
- ✦CLI and MCP/IDE integration for AI coding agents
- ✦Auto-healing tests when the UI drifts
- ✦Growing regression suite that persists across development phases
- ✦No-code web app with live preview and video replay for QA teams
- ✦AI-Powered Test Case Generation
- ✦Automated API Regression Testing
- ✦Collaborative Bug Tracking
- ✦Integrations with Project Management and CI/CD Tools
- ✦Effortless API Documentation
- ✦Unified Platform for Different Testing Phases
- →Debugging failed Stripe, GitHub or Shopify webhooks
- →Recovering dropped events
- →Monitoring webhook reliability
- →Alerting on failures before users notice
- →Shipping AI agents and web apps to production
- →Deploying the same app across many customer clouds
- →Agencies deploying into client cloud accounts
- →Avoiding hand-written Terraform or Kubernetes
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Verifying AI coding-agent output before merging code
- →Catching regressions from unattended overnight coding runs
- →QA teams testing live apps without writing test scripts
- →Gating CI/CD releases on end-to-end pass rates
- →AI-Powered Test Case Generation: Devzery’s AI engine analyzes your PRD or project details to generate API test cases.
- →Test Suite & HTTP Coverage Metrics: Track test coverage and HTTP distribution metrics to ensure all critical aspects of your APIs are covered.
- →Precise Bug Tracking with AI: Automatically generate detailed bug reports with status, related test cases, expected vs. actual results, and error descriptions.