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Text2SQL
✓ verifiedPaid
AI tool that converts natural-language questions into SQL queries, sold via a Lemon Squeezy storefront with tiered pricing.
👁 20K/mo♥ 14K
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Code Autopilot
✓ verifiedFreemium
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Pricing
Free Plan: $0 one-time
Hobby: $16/month
Standard: $83/month
Growth: $333/month
Auto Recharge Credits: $11/mo for 1000 credits
Credit Pack: $9/mo for 1000 credits
Enterprise Plan: Contact for Pricing
No public pricing
Text2SQL.AI: $7.00-$48.00
Text2SQL.AI Pro: $29.00-$228.00
Free trial available
No public pricing
No public pricing
Core features
- ✦Web scraping
- ✦Web crawling
- ✦Data extraction in Markdown, JSON, and screenshot formats
- ✦Dynamic content handling
- ✦Rotating proxies
- ✦Rate limits management
- ✦Open-source availability
- ✦Media Parsing
- ✦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)
- ✦Natural language to SQL query generation
- ✦Standard and Pro subscription tiers
- ✦Checkout and billing via Lemon Squeezy
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- ✦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
- →Powering AI assistants with real-time web content
- →Enhancing sales data with web information
- →Adding scraping capabilities to code editors
- →Enabling customers to build AI apps with web data
- →Extracting comprehensive information for in-depth research
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Generating SQL queries without writing raw syntax
- →Helping non-technical users query databases
- →Speeding up ad hoc data lookups for analysts
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- →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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