Shaped Personalization

Shaped is an end-to-end relevance engine designed for real-time personalization and agent memory. It allows users to connect their data, train machine learning models, and query text, user, or session context to retrieve relevant results in milliseconds. The platform utilizes ShapedQL, a SQL-like interface, to compile queries into optimized, multi-stage ranking pipelines, enabling hybrid search, filtering, ML-driven scoring, and reordering for diversity and exploration. This engine is built for product and engineering teams looking to enhance engagement and revenue through personalized experiences. It supports a wide range of use cases including personalized content feeds, hybrid search and discovery, AI agent retrieval, similar item recommendations, and dynamic email content. Shaped aims to replace traditional document retrieval with a system that treats user context as a first-class input, offering faster experimentation velocity and rapid deployment of new ranking models. Shaped integrates with over 30 data connectors, including data warehouses, analytics applications, and streaming platforms, allowing for the unification of batch and real-time data. It provides enterprise-grade security and compliance (SOC 2 Type II, GDPR/HIPAA) and is designed for scalability and reliability, handling billions of requests and millions of users and items with low latency.