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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 lab providing expert human data, RL environments, and contextual evaluations to train and assess AI models and agents.
No public pricing
No public pricing
Free trial available
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)
- ✦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
- ✦Realm: RL environments and frontier evaluations
- ✦Cortex: contextual evaluation for production AI agents
- ✦Expert-demonstrated robotics training data
- ✦Benchmarks such as LongExtractionBench
- ✦Expert human data partnerships
- ✦Research lab on human data markets
- →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
- →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
- →Train and evaluate frontier AI models
- →Improve agent performance in production
- →Source expert human data for AI labs
- →Gather demonstration data for robotics