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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
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.
Browser-based AI dev workspace by Google for full-stack apps; being sunset on 22 Mar 2027, no new workspaces.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
No public pricing
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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)
- ✦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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →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
- →Prototyping apps from a prompt or mockup
- →Building full-stack apps in the browser
- →Collaborating and sharing preview URLs
- →Deploying and monitoring apps quickly