Your structured data lives in PostgreSQL. But critical knowledge like contracts, policies, and research is stuck in files your database can’t access. Unstructured fixes that by turning raw documents into structured, vectorized data that works with AI and search, all inside PostgreSQL.
Turn Documents into AI-Ready Data
Most enterprise knowledge lives in unstructured formats—PDFs, images, Office docs, and more. Unstructured replaces brittle, manual pipelines with a scalable PostgreSQL-native solution that turns unstructured content into structured, vector-embedded data ready for GenAI, semantic search, and analytics.
Bring Unstructured Data into Your Database
PostgreSQL is your source of truth. Unstructured makes sure your unstructured data gets there clean, enriched, and ready for AI.
Key Features
- Built-in PostgreSQL Destination Connector
Write document outputs directly into your PostgreSQL database with one-line config via UI, API, or Python SDK. - pgvector Embedding Support
Generate and store embeddings inside PostgreSQL tables using the pgvector extension for fast similarity search and GenAI integration. - Smart Chunking & Metadata Enrichment
Automatically split documents into meaningful segments and enrich them with metadata, summaries, and entities. - Secure & Scalable
Enterprise-grade architecture with built-in access control, auditability, and support for large-scale ingestion.
Use Cases
Getting Started with Unstructured and PostgreSQL
Spin up your Unstructured + PostgreSQL workflow in minutes with our quickstart guides:
Relevant Blogs
Maria Khalusova, Paul Cornell
We’re Here to Help
Turn PostgreSQL into your GenAI engine. With Unstructured, unstructured files become structured, embedded, and instantly usable for search and chat to agents and analytics.
