ZeroEntropy

The Engine For Human-Level Search.

Free Trial

Description

ZeroEntropy is an advanced AI retrieval engine designed to deliver human-level search capabilities through a unified API. It addresses common frustrations with retrieval layer latency and accuracy, offering a solution for AI Agents and RAG applications that is fast, context-aware, and precise. The platform aims to simplify the traditionally complex process of building search functionalities, allowing developers to integrate cutting-edge retrieval into their products quickly.

By learning from every query and interaction, ZeroEntropy continuously improves its performance, adapting to user intentions and evolving to provide increasingly relevant results. It autonomously selects optimal retrieval strategies, eliminating the need for manual tuning of components like vector databases, pipelines, and rerankers. This approach significantly reduces engineering overhead, freeing up teams to focus on core product development while ensuring high-quality, self-improving search experiences.

Key Features

Adaptive Retrieval: Dynamically chooses optimal retrieval strategies based on context.
Context-Aware Understanding: Interprets data holistically, query context, and user intentions.
Self-Improving Engine: Continuously learns from queries and interactions to enhance relevance.
Unified Search API: Combines dense, sparse, and reranked relevance in a single interface, simplifying integration.
Enterprise-Grade Security: Features SOC 2 Type II compliance and HIPAA readiness for data protection.
Automated Optimization: Eliminates the need for manual tuning of weights, thresholds, and configurations.
Reduced Infrastructure Management: Unifies vector DBs, LLMs, and pipelines into a single managed service, saving engineering time.

Use Cases

Powering AI Agents with fast and accurate information retrieval.
Enhancing Retrieval Augmented Generation (RAG) systems for better contextual responses.
Building intelligent chatbots capable of understanding complex queries.
Improving internal knowledge base search functionality for enterprises.
Delivering personalized and adaptive search experiences within applications.

Frequently Asked Questions

What makes ZeroEntropy different from traditional search engines?

Traditional search uses static keyword or semantic matching. ZeroEntropy is optimized for retrieval quality out of the box — combining dense, sparse, and reranked relevance in a single API. We treat every query as a learning opportunity: You get state-of-the-art relevance, not a bag-of-words match. You don’t need to tune BM25 weights, vector thresholds, or rerank configs — we handle that. You don’t maintain an infra Frankenstein of vector DBs, LLMs, pipelines — we unify it.