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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.
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
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
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
- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
- ✦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
- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
- →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