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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Headless, open-source rich-text editor framework with paid add-ons for collaboration, comments, AI editing agents and document conversion.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
Free trial available
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦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
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
- ✦Headless, extensible core editor with 100+ extensions
- ✦Real-time collaborative editing with live cursors
- ✦Inline and document comments
- ✦DOCX, ODT and Markdown import/export
- ✦AI Toolkit for building document-editing AI agents
- ✦Prebuilt UI components and editor templates
- ✦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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →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
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
- →Building a custom rich-text editor for a SaaS product
- →Adding real-time collaboration to a document app
- →Letting an AI agent edit documents with tracked changes
- →Importing or exporting Word or Markdown content in-app
- →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
