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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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Text2SQL
✓ verifiedFreemium
Converts natural language into SQL across databases; useful real dev tool.
👁 20K/mo♥ 14K
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Apify
✓ verifiedFreemium
Full-stack platform for web scraping, data extraction, and automation; category leader.
👁 4.4M/mo♥ 2.0K
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Code Autopilot
✓ verifiedFreemium
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Pricing
No public pricing
Basic: $8 USD / month billed annually ($4)
Pro: $25 USD / month billed annually ($19)
Enterprise: Custom USD / month
No public pricing
Free: $0/mo ($5 included usage)
Starter: $29/mo ($26/mo billed annually)
Scale: $199/mo ($179/mo billed annually)
Business: $999/mo ($899/mo billed annually)
Free trial available
No public pricing
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Text to SQL conversion
- ✦AI query generation, explanation, fixing, and optimization
- ✦Support for multiple database types
- ✦Database schema integration for accuracy
- ✦Public API for integration with other tools
- ✦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)
- ✦Web scraping
- ✦Data extraction
- ✦Browser automation
- ✦AI agents
- ✦Anti-blocking
- ✦Proxy rotation
- ✦Open-source tools (Crawlee)
- ✦Ready-made tools and code templates
- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Generating SQL queries from natural language descriptions
- →Explaining complex SQL queries
- →Fixing errors in existing SQL code
- →Optimizing SQL queries for performance
- →Building custom SQL AI tools using the API
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Data for generative AI
- →Lead generation
- →Market research
- →Sentiment analysis
- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
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