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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
AI-powered IDE with code completion, generation, explanation and debugging, plus a cloud dev environment, for developers.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
No public pricing
Free trial available
No public pricing
Free trial available
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦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
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦AI code completion and snippet generation
- ✦Natural-language code generation
- ✦Code explanation and AI Q&A
- ✦Automated bug detection and fixes
- ✦Zero-config cloud development environment
- ✦Project creation from templates or Git
- ✦Automatic context-gathering from connected engineering sources
- ✦AI-generated code, tests and pull requests from tickets
- ✦Task planning that breaks complex work into subtasks
- ✦Auto-updating engineering documentation
- ✦Vector search over embedded project data
- ✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
- ✦Engineering productivity analytics dashboard
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →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
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Writing and completing code faster with AI
- →Onboarding to unfamiliar codebases
- →Debugging and optimizing code
- →Spinning up dev environments in the browser
- →Engineering teams automating ticket-to-PR workflows
- →Developers wanting AI-assisted debugging and test generation
- →Engineering managers tracking AI-driven productivity gains
- →Teams centralizing documentation from scattered sources