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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Data-annotation platform with AI-assisted labeling tools and team workflows for building ML training datasets.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Visual development platform with AI design-to-code, a visual editor and headless CMS so teams and agents ship UI in real code.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
No public pricing
- ✦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
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦AI-assisted data annotation tools
- ✦Training-data platform (BasicAI Cloud)
- ✦Team and project management
- ✦Annotation services
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦AI design-to-code (Figma to code)
- ✦Visual editor tied to your components
- ✦Headless/visual CMS
- ✦AI agents (Builder-Agent) that open PRs
- ✦Integrations: GitHub, GitLab, Bitbucket, Figma, VS Code
- ✦Roles, reviews and collaboration
- →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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Labeling images and data for ML models
- →Managing annotation teams and projects
- →Producing training datasets at scale
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Convert designs to production code
- →Let non-developers edit pages visually
- →Manage content with a headless CMS
- →Collaborate across design, PM and engineering