Unstructured and Weaviate Partner to Streamline Document-Aware AI

Unstructured and Weaviate have partnered to help teams build intelligent, transparent AI systems grounded in the structure and semantics of real-world documents. This collaboration combines Unstructured with Weaviate’s flexible and scalable vector database—making it easier to move from raw enterprise content to production-grade retrieval and agentic systems.

Integration Capabilities

Together, these platforms offer a composable and developer-friendly foundation for GenAI systems that need to reason over complex formats like legal contracts, scientific papers, webpages, and business documents. From document parsing to semantic retrieval, the Unstructured × Weaviate integration is designed for real-world complexity and scale.

Developer Use Cases

This integration supports parsing, chunking, enrichment, and retrieval in a single streamlined pipeline. You can parse documents with layout and semantic awareness, enrich content with tables and named entities, embed using state-of-the-art models, and index directly into Weaviate for fast, filtered search.

The Unstructured × Weaviate integration is built for teams that need transparent, scalable, and composable AI infrastructure. Whether you’re launching a chatbot, building a legal AI assistant, or deploying a global document intelligence pipeline, this stack helps you bridge raw content and context-aware AI.

Need help getting started? Get in touch to talk through your use case.