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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
AI agent-based end-to-end testing platform for SaaS teams that runs exploratory and PR-triggered tests without maintaining test scripts.
Vercel's AI app builder that generates and deploys full-stack React web apps and UI components from natural-language prompts.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
Free trial available
- ✦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 with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦AI agents that visually explore and test UI like a real user
- ✦Automatic PR-triggered test runs via GitHub/Vercel preview integration
- ✦Self-healing tests that adapt to UI and workflow changes
- ✦Mobile web, iOS, and Android app testing support
- ✦Detailed debugging with screenshots, logs, and failure reasoning
- ✦Cloud-native execution with no source-code access required
- ✦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
- ✦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
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Engineering teams wanting regression testing without maintaining scripts
- →SaaS companies needing continuous QA feedback on every pull request
- →Teams replacing manual QA hours with automated agent-driven testing
- →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
- →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