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Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Ai2's family of fully open language models with weights, code, and training data released, built for transparent LLM research and building.
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
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
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Fully open weights, code, and training data
- ✦Base, Think (reasoning), and Instruct variants
- ✦7B and 32B model sizes
- ✦Open model flow across all training stages
- ✦Open-source training/eval tools (OlmoCore, OLMES)
- ✦OlmoTrace to trace outputs to training data
- →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
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Researching language-model training and behavior
- →Building and fine-tuning open models
- →Machine-unlearning and clinical-NLP research
- →Deploying transparent open LLMs