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Premium Figma and Framer UI kit with hundreds of components, variants and icons for building polished, themeable sites.
Data-annotation platform with AI-assisted labeling tools and team workflows for building ML training datasets.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
Free, local, open-source AI app builder that works with any AI model and exports real code you own, with zero lock-in.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦300+ Figma UI components
- ✦2,000+ Figma variants
- ✦2,116 icons
- ✦Framer-ready components and templates
- ✦Deep theming (glass, line, flat styles)
- ✦Adaptive layouts with variables
- ✦AI-assisted data annotation tools
- ✦Training-data platform (BasicAI Cloud)
- ✦Team and project management
- ✦Annotation services
- ✦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
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Local-first, open-source app building
- ✦Works with any AI model or provider
- ✦Exports real, ownable code (no lock-in)
- ✦Supabase database, auth, and server functions
- ✦Built-in security review and fixes
- ✦Deploy to GitHub and Vercel; MCP server support
- →Build a website or app UI in Figma
- →Hand off Figma designs to Framer
- →Speed up prototyping with prebuilt components
- →Labeling images and data for ML models
- →Managing annotation teams and projects
- →Producing training datasets at scale
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Building full-stack apps with your own AI models
- →Prototyping without proprietary platform lock-in
- →Adding database and auth via Supabase
- →Deploying apps to GitHub and Vercel