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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
AI co-pilot for technical diagrams and design docs, with diagram-as-code and integrations for engineering teams.
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
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦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
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- ✦AI-generated diagrams from prompts
- ✦Diagram-as-code editing
- ✦Markdown design docs
- ✦Eraserbot auto-updating codebase diagrams
- ✦Integrations: GitHub, Notion, Confluence, VS Code
- ✦Export to PNG/SVG/PDF/MD and MCP server
- →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
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →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
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- →Create architecture and cloud diagrams fast
- →Write and maintain design docs
- →Keep codebase diagrams up to date
- →Embed live diagrams in Notion/Confluence
