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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Fast AI code-completion tool with a 1M-token context window, offering free and paid tiers for individuals and teams.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
Free trial available
- ✦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
- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦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
- ✦Low-latency AI code completions
- ✦1 million token context window for large codebases
- ✦IDE support for VS Code, JetBrains, and Neovim
- ✦Built-in chat with multiple model options
- ✦One-click diff/apply for AI-suggested changes
- ✦Automatic error-fixing using compiler diagnostics
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →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
- →Solo developers wanting a fast, free code-completion tool
- →Professional developers working in large codebases needing more context
- →Engineering teams standardizing on one AI coding assistant with central billing