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ShapedQL

Freemium
www.shaped.ai

The SQL engine for search, feeds, and AI agents

Developer ToolsSoftware EngineeringArtificial Intelligence
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ShapedQL screenshot
Added on January 29, 2026← Back to all tools

What does this tool do?

ShapedQL is a sophisticated SQL-like query engine designed for advanced search, recommendation, and retrieval tasks. It allows developers to build complex, AI-powered ranking systems using a SQL-like syntax that goes beyond traditional document retrieval. The tool enables multi-source retrieval, combining semantic search, keyword matching, and machine learning models to generate highly relevant and personalized results across various use cases like social feeds, e-commerce recommendations, and content discovery.

AI analysis from Feb 18, 2026

Key Features

  • Hybrid search across multiple indexes
  • Machine learning model integration for ranking
  • User context as a first-class input
  • Dynamic diversity and exploration controls
  • Real-time retrieval engine
  • SOC 2 Type 2 security compliance
  • Extensive connector ecosystem

Use Cases

  • 1Personalized social media content feeds
  • 2E-commerce product recommendations
  • 3Semantic search across complex data sources
  • 4AI agent retrieval and memory systems
  • 5Hybrid search with multiple ranking criteria
  • 6Content recommendation platforms
  • 7User-context-aware search engines

Pros & Cons

Advantages

  • SQL-like query syntax makes complex retrieval accessible
  • Sub-50ms query latency for real-time applications
  • Native support for machine learning model integration
  • Supports multi-stage ranking and filtering
  • Flexible retrieval across multiple data sources

Limitations

  • Requires technical expertise to fully leverage
  • Learning curve for developers unfamiliar with advanced retrieval concepts
  • Potential complexity in model training and setup

Pricing Details

$300 free credits, no credit card required. Specific tier pricing not publicly displayed on website.

Who is this for?

Machine learning engineers, AI developers, product teams building recommendation systems, search platforms, and personalized content applications

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