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What is Shaped?

Shaped is a real-time context engine designed for agentic AI, built by a team focused on reducing the cost and complexity of AI agent retrieval. It solves the problem of high latency and poor relevance in traditional RAG stacks by unifying retrieval, ranking, and learning into a single query. Core capabilities include personalized hybrid search, multi-stage ranking with ML models, and a feedback loop that improves results over time. The tool supports querying by text, user ID, or item ID, and integrates with over 30 native connectors. It is ideal for product and engineering teams building personalized feeds, search, recommendations, and AI assistants. Shaped claims to reduce agent costs from $1.50 to $0.03 per answer by eliminating retries and providing right-first-time results. It offers a SQL-like interface called ShapedQL and provides SDKs for Python, TypeScript, and MCP.

AI Tool Review Summary

Performance Score

4.7/5

Content/Output Quality

High, consistent, and personalized

Interface

Clean and developer-friendly

AI Technology
LLMNLPMachine Learning
Purpose of Tool

Real-time context engine for personalized retrieval and agent memory.

Compatibility

Integrates with 30+ data sources including Snowflake, BigQuery, Kafka, and Postgres.

Pricing

Freemium with $100 free credits, then usage-based pricing

Features

Features with the highest value for users are highlighted here.

ShapedQL unified query language

Hybrid semantic and keyword search

Personalized results per user

Feedback loop for continuous learning

Sub-50ms query latency

30+ native data connectors

Multi-stage ranking pipeline

Enterprise-grade security and compliance

Who Is It For?

Product teams

Engineering teams

AI/ML engineers

Data scientists

E-commerce companies

Media & streaming platforms

SaaS companies

Startups

Enterprise organizations

AI assistant developers

Pricing

Free

$0/monthly
  • $100 free credits
  • Up to 1M queries/month
  • Community support
Popular

Pro

$99/monthly
  • 10M queries/month
  • Priority support
  • Advanced analytics

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Pros & Cons

Pros

  • Dramatically reduces agent costs by providing accurate context on the first call.
  • Unifies retrieval, ranking, and learning in a single query, simplifying the stack.

Cons

  • May require significant data integration effort to fully leverage personalization.
  • Pricing details are not transparently listed on the website.

FAQs

Just Launched

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Quick Shaped Comparision

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