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AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
Converts screenshots, PDFs, and slides into editable Figma, PowerPoint, or Canva designs and turns Figma layouts into code.
AI design-to-code tool that converts Figma designs or cloned websites into HTML/React and builds apps with vibe coding.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Data labeling across modalities
- ✦RL environments and reward signals
- ✦Custom model evaluations and benchmarks
- ✦Human preference/annotation from an expert network
- ✦Recursion RL platform for enterprise agents
- ✦Robotics data (video, trajectories)
- ✦Screenshot-to-editable-design conversion
- ✦NoteSlide: PDF and image slides to editable PowerPoint or Keynote
- ✦Figma-to-code generation
- ✦Image-to-vector/SVG and PSD/web-to-Figma import
- ✦Visual Struct API for developers
- ✦Codia AI Vision layout and typography reconstruction
- ✦Figma-to-code (HTML/React)
- ✦Clone any or private website to code
- ✦AI website and app builder
- ✦Figma agent (Buddy) and design agent
- ✦Anima MCP server and API
- ✦Adobe XD support
- →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
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
- →Rebuild UI screenshots into editable Figma layers
- →Turn NotebookLM PDFs into editable decks
- →Convert images and posters into reusable design assets
- →Move designs between Figma and Canva
- →Extract layout structure via API
- →Converting Figma designs to code
- →Cloning sites as starting points
- →Building web apps with AI
- →Automating design-to-code in dev workflows