Unstructured
and IBM

Drive faster, smarter AI outcomes by transforming unstructured content into structured, governed insights with IBM and Unstructured.

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Convert unstructured content into AI-ready data.

Transform documents, PDFs, and images into structured, searchable intelligence that accelerates retrieval, analytics, and AI outcomes. With IBM and Unstructured, enterprises gain a simple, secure way to prepare content for AI at scale.
​​Comprehensive connectivity and format support​

Unstructured connects to 30+ enterprise data sources and supports 70+ file types, transforming PDFs, images, and emails into AI-ready data. Its intelligent parsing preserves structure and meaning for higher-quality inputs to watsonx.data. 

 
​Accelerated pipeline development​

No-code workflows and a developer API simplify data ingestion and transformation. Automated syncs and multi-source orchestration keep pipelines fresh, lower compute costs, and speed AI deployment.

 
Enterprise-grade governance and compliance​​​

SOC 2 Type II, HIPAA, ISO 27001 and GDPR compliance ensure data security from source to output. Integrated lineage tracking and version control extend watsonx.data’s trusted governance framework.
​Optimized for AI workflows​

Unstructured enriches and chunks unstructured content into model-ready data, enabling watsonx.data to power hybrid RAG, fine-tuning, and agentic AI with accuracy and scale.

Features

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Natively mount and stream files from enterprise storage platforms, business tools, and collaboration systems—no third-party connectors required. Support for 70+ file formats with OCR, visual-language parsing, and table extraction built in.

 

 
Illustration of a man holding a magnifying glass in front of a search bar

Prepare your data for embedding with semantically enriched, chunked content. Enable fast, precise search across IBM Milvus or other vector search engines.
Screenshot of the AutoAI for RAG website

Automatically generate retrieval-optimized content chunks enriched with summaries, metadata, captions, and structured entities—ideal for use in GenAI and agent workflows.

 
Isometric illustration of data storage and cloud computing concepts.

Secure by design. Built for scale with declarative workflows, configurable pipelines, and governance-first principles.

 
Two cartoon file folders holding hands

Deploy Unstructured with IBM watsonx.data or any preferred storage and vector database stack. Output formats are schema-aligned and metadata-rich for easy downstream consumption. 

 

 

 
Illustration of a soccer player sliding on the ground with papers

Natively mount and stream files from enterprise storage platforms, business tools, and collaboration systems—no third-party connectors required. Support for 70+ file formats with OCR, visual-language parsing, and table extraction built in.

 

 
Illustration of a man holding a magnifying glass in front of a search bar

Prepare your data for embedding with semantically enriched, chunked content. Enable fast, precise search across IBM Milvus or other vector search engines.
Screenshot of the AutoAI for RAG website

Automatically generate retrieval-optimized content chunks enriched with summaries, metadata, captions, and structured entities—ideal for use in GenAI and agent workflows.

 
Isometric illustration of data storage and cloud computing concepts.

Secure by design. Built for scale with declarative workflows, configurable pipelines, and governance-first principles.

 
Two cartoon file folders holding hands

Deploy Unstructured with IBM watsonx.data or any preferred storage and vector database stack. Output formats are schema-aligned and metadata-rich for easy downstream consumption. 

 

 

 

Use cases

A collection of four distinct graphs
Hybrid RAG (RAG++)

Deliver semantically chunked, high-quality enterprise content to your GenAl models. Data is retrieved, enriched, and governed entirely within the watsonx ecosystem. 

 

 

 
LLM Fine-Tuning & Evaluation

Generate training and evaluation datasets from raw enterprise files. Structure and enrich content for use in model development and experimentation through watsonx.data. 

 

 

 
Illustration of a central speech bubble surrounded by various icons and symbols
AI agent workflows

Equip agents with structured knowledge extracted from contracts, policies, and presentations. All content is versioned and stored within watsonx.data for access, traceability, and reuse. 

  
An open hand with various data visualization icons floating above it
Enterprise search

Transform fragmented legacy files into structured, searchable knowledge. Enable semantic and keyword search across internal platforms and the IBM watsonx portfolio.
A collection of four distinct graphs
Hybrid RAG (RAG++)

Deliver semantically chunked, high-quality enterprise content to your GenAl models. Data is retrieved, enriched, and governed entirely within the watsonx ecosystem. 

 

 

 
LLM Fine-Tuning & Evaluation

Generate training and evaluation datasets from raw enterprise files. Structure and enrich content for use in model development and experimentation through watsonx.data. 

 

 

 
Illustration of a central speech bubble surrounded by various icons and symbols
AI agent workflows

Equip agents with structured knowledge extracted from contracts, policies, and presentations. All content is versioned and stored within watsonx.data for access, traceability, and reuse. 

  
An open hand with various data visualization icons floating above it
Enterprise search

Transform fragmented legacy files into structured, searchable knowledge. Enable semantic and keyword search across internal platforms and the IBM watsonx portfolio.
Take the next step

Transform how your teams access and apply knowledge by converting enterprise content into trusted data for AI and analytics with IBM and Unstructured.