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AI-powered code editor with agentic workflows for developers.
AI-powered IDE with code completion, generation, explanation and debugging, plus a cloud dev environment, for developers.
Open-source terminal AI pair programmer that edits code in your local git repo and auto-commits, working with most LLMs.
AI coding assistant with multi-model chat and developer tools to help write, explain and improve code faster.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- ✦AI code completion and snippet generation
- ✦Natural-language code generation
- ✦Code explanation and AI Q&A
- ✦Automated bug detection and fixes
- ✦Zero-config cloud development environment
- ✦Project creation from templates or Git
- ✦Terminal-based AI pair programming
- ✦Edits code in your local git repo
- ✦Automatic git commits with messages
- ✦Codebase mapping for large projects
- ✦Works with cloud and local LLMs
- ✦Voice-to-code, image/web context, lint and test
- ✦AI code generation
- ✦Multi-model chat
- ✦Developer utility tools
- ✦Code explanation and improvement
- ✦Automatic context-gathering from connected engineering sources
- ✦AI-generated code, tests and pull requests from tickets
- ✦Task planning that breaks complex work into subtasks
- ✦Auto-updating engineering documentation
- ✦Vector search over embedded project data
- ✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
- ✦Engineering productivity analytics dashboard
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow
- →Writing and completing code faster with AI
- →Onboarding to unfamiliar codebases
- →Debugging and optimizing code
- →Spinning up dev environments in the browser
- →Building features and fixing bugs via AI in the terminal
- →Working on large existing codebases
- →Automating git commits
- →Using local LLMs for private coding
- →Writing code faster
- →Explaining or debugging code
- →Generating tests and documentation
- →Engineering teams automating ticket-to-PR workflows
- →Developers wanting AI-assisted debugging and test generation
- →Engineering managers tracking AI-driven productivity gains
- →Teams centralizing documentation from scattered sources