Unlock the Power of
Unstructured Data for AI with
Vector Search

Milvus and Zilliz data connectors make unstructured data from 1,000+ sources instantly accessible and AI-ready, powering your GenAI applications with vector search for smarter insights.

Why Master Unstructured Data for AI with Vector Search?

Unlock Hidden Insights
Unstructured data, such as text, images, and videos, contains complex, untapped insights that traditional analytics can't access. Vector similarity search enables AI to uncover hidden patterns and trends within these formats, helping businesses identify new opportunities, make smarter decisions, and gain a unique competitive edge that only unstructured data analysis can provide.
Break Down Data Silos
Every day, vast amounts of unstructured data—emails, customer interactions, documents—are created and locked away in data silos across different platforms. Milvus and Zilliz data connectors break down these barriers, seamlessly channeling data from over 1,000 sources into an AI-ready format for smarter and more efficient insights through vector search.
Build GenAI with Vector Search
Vector search goes beyond traditional search methods such as keyword matching by mapping unstructured data into context-rich, searchable vector embeddings from deep learning models. This enables your GenAI applications to uncover hidden patterns and relationships within your data, delivering smarter, more relevant insights in real time.

Seamlessly Connect 1,000+ Unstructured Data Sources to Milvus and Zilliz Cloud for Scalable, AI-Powered Search

Milvus and its managed service, Zilliz Cloud, are scalable, AI-native vector databases designed to handle massive datasets. Now integrated with leading data streaming platforms, they offer robust connectors that seamlessly connect, stream, store, and retrieve unstructured data from any source. This makes it easy to build advanced AI applications like Retrieval-Augmented Generation (RAG) and more.