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Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Browser-based AI dev workspace by Google for full-stack apps; being sunset on 22 Mar 2027, no new workspaces.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
No public pricing
No public pricing
No public pricing
No public pricing
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)
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦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
- ✦Cloud workspaces for full-stack development
- ✦App Prototyping agent from natural language
- ✦Gemini AI for coding, debugging and docs
- ✦Repo import from GitHub, GitLab and Bitbucket
- ✦Web previews and Android emulators
- ✦Deploy to Firebase App Hosting, Hosting or Cloud Run
- ✦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)
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Prototyping apps from a prompt or mockup
- →Building full-stack apps in the browser
- →Collaborating and sharing preview URLs
- →Deploying and monitoring apps quickly
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents