Unstructured AI

Preparing Unstructured Documents for AI

Unstructured AI is an open-source library and managed API service for parsing and cleaning unstructured documents to prepare them as high-quality input for LLM applications. It addresses a fundamental challenge in building AI applications: the data organizations want to use is trapped in PDFs, Word documents, HTML pages, images, and other unstructured formats that language models cannot directly consume.

Document Processing for AI Pipelines

Unstructured extracts clean, structured text from a wide variety of document formats and returns it in a consistent, normalized format. Crucially, it also performs document chunking — intelligently splitting documents into appropriately sized segments that respect semantic boundaries like paragraphs and sections, rather than naively splitting on character count. This chunking quality directly affects RAG system performance.

• Supports 20+ document formats including PDF, DOCX, HTML, images
• Intelligent semantic chunking for RAG applications
• Element classification (text, table, title, figure)
• OCR for image-based documents
• Cloud API and self-hosted deployment options

Infrastructure for the LLM Stack

Unstructured is used as the document ingestion layer in LLM applications at companies ranging from startups to large enterprises. Its open-source nature has built a large community, while the managed API service provides the reliability and scale required for production workloads without operational overhead.