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Devv.AI
✓ verifiedPaid
AI search engine for developers with code repo integration.
52K visits/mo4.2K saves
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Void Editor
✓ verifiedFree
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
Pricing
No public pricing
No public pricing
Historical Data Pack: $49.9
Base Plan: $14.9/month
Advanced Plan: $24.9/month
Enterprise Plan: $34.9/month
No public pricing
No public pricing
Core features
- ✦GitHub Mode for repository search
- ✦Web Mode for web-based information retrieval
- ✦Chat Mode for direct AI interaction
- ✦Model selection (GPT, Claude, Gemini)
- ✦Student discount program
- ✦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)
- ✦Commits and Pull Requests Dashboard
- ✦Advanced Developer Skills Analysis
- ✦Strategic Investment Balance Monitoring
- ✦Collaborative Developers Map
- ✦Benchmarking Comparison with Other Teams
- ✦Smart Notifications
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- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
Use cases
- →Writing API reference documentation
- →Brainstorming SEO strategies
- →Enhancing code functionality
- →Gaining insights into open-source projects
- →Resolving complex code issues
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Visualize historical graphs of code evolution
- →Assess development team performance using RSI and EMA
- →Understand developer skills and identify areas for improvement
- →Categorize commits by type (fixes, refactoring, etc.) to analyze investment balance
- →Identify individual and collective contributors within the team
- →Compare team performance with industry benchmarks
- →Receive weekly and monthly reports with AI-extracted insights
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- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help
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