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Kiro AI
✓ verifiedFreemium
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
3.8M visits/mo
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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 visits/mo14K saves
Pricing
No public pricing
Free: $0/mo (50 credits)
Pro: $20/user/mo (1,000 credits)
Pro+: $40/user/mo (2,000 credits)
Pro Max: $100/user/mo (5,000 credits)
Power: $200/user/mo (10,000 credits)
Text2SQL.AI: $7.00-$48.00
Text2SQL.AI Pro: $29.00-$228.00
Free trial available
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
Core features
- ✦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)
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦Natural language to SQL query generation
- ✦Standard and Pro subscription tiers
- ✦Checkout and billing via Lemon Squeezy
- ✦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
- ✦Digital Asset Management (DAM)
- ✦Media Asset Management (MAM)
- ✦AI-powered automation
- ✦Cloud, on-premises, or hybrid deployments
- ✦Integration with Adobe Creative Cloud, Cinema 4D, Sketch, and more
- ✦Version control
- ✦Fast search
- ✦Custom brand portals
- ✦Analytics
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Generating SQL queries without writing raw syntax
- →Helping non-technical users query databases
- →Speeding up ad hoc data lookups for analysts
- →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
- →Managing work-in-progress images, graphics, layouts, and documents.
- →Automating video workflows, including transcoding and archiving.
- →Identifying objects, faces, logos, and scenes in media using AI.
- →Generating speech-to-text for search and closed captioning.
- →Creating rough video cuts instantly with AI.
- →Managing campaign assets and distributing them to various endpoints.
- →Enabling secure collaboration for remote and on-premises teams.
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