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Software Development__code Generation__frontend GenerationSoftware Development__code Generation__full Stack App GenerationSoftware Development__coding Assistants Copilots__ide CopilotsSoftware Development__coding Assistants CopilotsSoftware Development__code GenerationSoftware DevelopmentAI AgentAI Assistant
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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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BasicAI Cloud
✓ verifiedFreemium
Data-annotation platform with AI-assisted labeling tools and team workflows for building ML training datasets.
👁 22K/mo
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Angular.dev
✓ verifiedFree
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
👁 1.1M/mo
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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)
- ✦AI-assisted data annotation tools
- ✦Training-data platform (BasicAI Cloud)
- ✦Team and project management
- ✦Annotation services
- ✦Design canvas integrated directly into the IDE (VSCode/Cursor)
- ✦Agent-driven MCP canvas based on open design format
- ✦AI Multiplayer for generating screens and flows in parallel
- ✦Design as Code: Design files live in repo, versioned with Git
- ✦Pixel-perfect vector-to-code workflow
- ✦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
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Labeling images and data for ML models
- →Managing annotation teams and projects
- →Producing training datasets at scale
- →Designing new products and features with pixel-perfect precision without leaving the development environment.
- →Eliminating design handoffs by having design and code live under one roof.
- →Accelerating workflow by using AI multiplayer to generate UI components and flows.
- →Shipping production-ready apps with guaranteed code-design alignment.
- →Integrating existing design systems directly from the codebase.
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
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