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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
AI-native test automation that generates, self-heals and runs UI, API and AI-agent tests across browsers and devices.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
Jira-native tool that turns existing issues into customer roadmaps, release notes, and feedback portals without duplicate data entry.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦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
- ✦AI-generated test cases for web, mobile, API and databases
- ✦Self-healing tests that patch selector drift
- ✦AI agent testing with adversarial scenarios and scoring
- ✦Parallel cloud grid across Chromium, Firefox, WebKit, iOS, Android
- ✦MCP to drive testing from Claude, ChatGPT or Cursor in plain English
- ✦Root cause analysis and visual regression
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Roadmaps synced live from Jira issues
- ✦AI-generated release notes
- ✦Customer feedback and idea portals
- ✦Audience-specific roadmap views
- ✦Password-protected or invite-only sharing
- ✦Publishing to Confluence and Slack
- →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
- →Automate end-to-end regression without hand-writing scripts
- →Validate AI agents on Agentforce, Bedrock or Azure AI before launch
- →Run cross-browser tests inside existing CI/CD pipelines
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Sharing a public product roadmap with customers
- →Publishing release notes automatically from Jira tickets
- →Collecting and prioritizing customer feature requests
- →Giving executives a curated view of product progress