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Software Development__dev Infrastructure__code Docs Review__documentation PlatformsSoftware Development__code Generation__sql Query GenerationSoftware Development__dev Infrastructure__code Docs ReviewSoftware Development__code GenerationSoftware Development__dev InfrastructureSoftware DevelopmentAI AgentAI Assistant
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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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The New GitBook
✓ verifiedFreemium
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
👁 653K/mo♥ 2.9K
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Released
✓ verifiedFreemium
Jira-native tool that turns existing issues into customer roadmaps, release notes, and feedback portals without duplicate data entry.
👁 11K/mo♥ 941
Pricing
Text2SQL.AI: $7.00-$48.00
Text2SQL.AI Pro: $29.00-$228.00
Free trial available
No public pricing
No public pricing
Free trial available
Free: $0/mo (up to 10 users, 2,000 AI tokens/user)
Standard: $1.10/user/month (unlimited users, 10,000 AI tokens/user)
Advanced: $1.70/user/month (unlimited users, 20,000 AI tokens/user)
Free trial available
Core features
- ✦Natural language to SQL query generation
- ✦Standard and Pro subscription tiers
- ✦Checkout and billing via Lemon Squeezy
- ✦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)
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Roadmaps synced live from Jira issues
- ✦AI-generated release notes
- ✦Customer feedback and idea portals
- ✦Audience-specific roadmap views
- ✦Password-protected or invite-only sharing
- ✦Publishing to Confluence and Slack
Use cases
- →Generating SQL queries without writing raw syntax
- →Helping non-technical users query databases
- →Speeding up ad hoc data lookups for analysts
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Sharing a public product roadmap with customers
- →Publishing release notes automatically from Jira tickets
- →Collecting and prioritizing customer feature requests
- →Giving executives a curated view of product progress
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