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AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
Vercel's AI app builder that generates and deploys full-stack React web apps and UI components from natural-language prompts.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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)
- ✦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
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- ✦Prompt-to-app generation of full-stack web applications
- ✦One-click deployment to Vercel hosting
- ✦GitHub sync for pushing generated code to a repository
- ✦Visual design mode for fine-tuning generated UI
- ✦Prebuilt templates for apps, dashboards and landing pages
- ✦Agentic building with automatic database and API connections
- ✦iOS app for building and editing on mobile
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
- →Developers rapidly prototyping and deploying web apps
- →Teams generating UI components and design systems from prompts
- →Non-technical founders building MVPs without writing code
- →Students and hobbyists building and publishing small projects