shaped

shaped

Shaped is a fully-managed AI relevance engine and vector database with a built-in feedback loop that unifies retrieval, ranking, and continuous learning to power real-time personalization for search, recommendations, feeds, and agent memory.

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Free API
#477 in AI Agents (477 tools)
Just launched
Data reviewed Aug 18, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: AI Agents

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Free from $0 initial (one-time) - $100 free credits

Next step

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shaped

Shaped is an end-to-end relevance engine and vector database designed for real-time personalization, retrieval, ranking, and continuous learning. It offers Shaped Cloud, a fully-managed AI ranking platform that handles embeddings, models, and data freshness so teams can retrieve relevant results in milliseconds and personalize results per user using behavioral signals and business rules. Shaped emphasizes unified queries (ShapedQL), a feedback loop that improves results with every interaction, 30+ native connectors for batch and streaming data, SDKs (Python/TypeScript), and enterprise-grade security (SOC 2 Type II, GDPR/CCPA/HIPAA) with <50ms latency and a 99.95% uptime SLA.

AI-native personalization platform for building ranking models and personalized experiences.

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Key Features

ShapedQL (Queryable SQL Interface)

A SQL-like query interface to retrieve and rank across semantic and keyword searches, combine contexts (text, user ID, item ID), apply filters and business rules, and reorder results using models and diversity controls.

Personalized Hybrid Search

Blend semantic and keyword search and rerank results per user using behavioral signals like click-through-rate models and personalization for per-user relevance.

Feedback Loop & Continuous Learning

Built-in feedback loop where every interaction improves models and ranking, enabling continuous learning rather than static embeddings.

Managed Embeddings & Models

Shaped handles embeddings, models, and data freshness so teams do not need to manage the underlying ML pipelines.

30+ Native Connectors

Prebuilt connectors for warehouses, streaming, storage, and analytics to ingest batch and real-time data without custom ETL.

SDKs and Developer Tools

Client SDKs (Python, TypeScript) and MCP support to integrate Shaped into applications and pipelines.

Low Latency & Enterprise SLAs

Designed for production with <50ms latency and a 99.95% uptime SLA; SOC 2 Type II and compliance with GDPR/CCPA/HIPAA.

Multi-purpose Relevance Engine

One engine supports recommendations, search, agent retrieval/memory, feeds, personalized email, and A/B experimentation for ranking models.

Pricing

Free Tier Available

Initial $100 free credits available with no credit card required.

Free Credits

$0 initial (one-time) - $100 free credits
  • Initial $100 free credits
  • No credit card required

Use Cases

Search & Discovery

Hybrid search combining keyword and semantic relevance, reranked for personalization and business rules to improve discovery across catalogs and content.

Recommendations & Feeds

Personalized content feeds and product recommendations that adapt in real time to user behavior and improve with interactions.

Agent Retrieval & RAG

Power AI agents with contextual memory and retrieval for retrieval-augmented generation and agent workflows.

E-commerce Upsell & Cart Recommendations

Product recommendations, cart upsell, and personalized email content to drive conversions and revenue.

Similarity & Content-based Matching

Find similar items using content and behavioral similarity for related-items and 'more like this' experiences.

Integrations

Snowflake

Warehouse connector for batch data ingestion and unified schemas.

BigQuery

Warehouse connector for batch data ingestion and analytics integration.

Redshift

Data warehouse connector for ingestion and unified views.

Databricks

Connector for large-scale data workflows and streaming integration.

Amplitude

Analytics connector to import behavioral events for personalization and modeling.

Segment / Rudderstack

Customer data pipelines to stream events into Shaped for real-time personalization.

Kinesis / Kafka / Pub/Sub

Streaming connectors to ingest event streams in real time.

Postgres / MongoDB

Storage connectors for product and metadata ingestion.

Shopify

E-commerce platform connector for product/catalog ingestion and personalization.

Benefits

Real-time personalization that improves with every interaction via a built-in feedback loop.
Unifies retrieval, ranking, and learning in a single query to replace complex multi-service retrieval stacks.
Lower per-answer cost claims versus traditional stacks (example comparison shown: $0.03 per answer vs $1.50 per answer).
Fast time-to-experiment and deployment (time to first experiment ~7 days; connect data to production in under a week).
Enterprise readiness with SOC 2 Type II, GDPR/CCPA/HIPAA compliance, and a 99.95% uptime SLA.

Limitations

No verified limitations are available.

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Create an account and claim the free credits offer ($100 free credits; no credit card required).
  2. 2 Connect your data using one of 30+ native connectors (warehouses, streaming, storage, analytics).
  3. 3 Query and prototype with ShapedQL or use the Python/TypeScript SDK to integrate into your application.
  4. 4 Deploy ranking models and start collecting interaction feedback to enable continuous learning and personalization.

Support

docs

Official product documentation and developer guides available via the site's Docs link.

case studies

Customer case studies and proven results are available on the site (read case studies).

blog

Product updates and announcements via the company blog.

API

Available: Yes
Documentation:

API and SDK documentation available via the site's Docs (Python SDK, TypeScript SDK, ShapedQL).

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