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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.
Atlassian's Git repository hosting for teams with built-in CI/CD pipelines and tight Jira integration for code review and deployment.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
AI end-to-end testing for web and mobile: write tests in plain English; agents author and self-heal them.
No public pricing
Free trial available
No public pricing
Free trial available
- ✦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
- ✦Git repository hosting
- ✦Bitbucket Pipelines CI/CD
- ✦Pull requests and code review
- ✦Native Jira integration
- ✦Branch permissions and access controls
- ✦IP allowlisting and security features
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- ✦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
- ✦Plain-English E2E test authoring
- ✦AI agents that self-heal tests
- ✦Web, iOS, and Android testing
- ✦Regression, smoke, and PR testing
- ✦Runs locally, in CI, or hosted
- ✦CLI wizard for setup
- →Debugging failed Stripe, GitHub or Shopify webhooks
- →Recovering dropped events
- →Monitoring webhook reliability
- →Alerting on failures before users notice
- →Source code management
- →CI/CD automation
- →Team code review
- →DevOps for Jira-based teams
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Automating end-to-end QA
- →Gating deploys with smoke tests
- →Testing every pull request