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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.
Open-source, self-hostable AI coding agent with autocomplete, in-IDE chat and autonomous task execution for teams needing data control.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
No public pricing
No public pricing
Free trial available
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
- ✦Autonomous AI agent that plans and executes multi-step coding tasks
- ✦In-IDE chat for asking, editing, debugging and generating code
- ✦Real-time code autocompletion using retrieval-augmented generation
- ✦Repository search and analysis for context-aware execution
- ✦Integrations with GitHub, databases and CI/CD pipelines
- ✦Self-hosted/on-premise deployment option for data privacy
- ✦Support for choosing among different underlying LLMs
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- →Debugging failed Stripe, GitHub or Shopify webhooks
- →Recovering dropped events
- →Monitoring webhook reliability
- →Alerting on failures before users notice
- →Developer teams wanting an in-IDE autonomous coding agent
- →Organizations requiring on-premise/self-hosted AI coding tools for data control
- →Individuals doing 'vibe coding' with minimal manual coding
- →Teams fine-tuning an AI assistant to their own codebase
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations