Unstructured.io

Unstructured was founded in 2022 by Brian Raymond, based on the observation that a very significant share of the world's data exists in "unstructured" formats, meaning documents such as PDFs, Word documents, PowerPoint presentations, images, and various other file formats that don't have the clean, consistently organized structure of traditional structured database data, but that most AI and machine learning applications, particularly retrieval-augmented generation systems that ground large language model responses in a company's own proprietary documents, require this unstructured document content to first be extracted, cleaned, and converted into a more structured, consistently formatted form before it can be effectively used to train or ground AI models, a data preparation step that has historically required significant custom engineering effort given the enormous variety of different unstructured document formats and layouts that real-world enterprise document collections typically contain. Unstructured's platform provides tools and infrastructure that automate this document processing and structuring pipeline, handling the technically challenging work of extracting text, tables, images, and other content from a very wide range of unstructured document formats and layouts, and converting that extracted content into clean, consistently structured data appropriate for feeding into AI and machine learning applications, particularly the retrieval-augmented generation applications that have become an extremely common pattern for building enterprise generative AI applications that need to ground language model responses in a company's own proprietary documents and data rather than relying solely on the model's general training data. The company has positioned its document processing infrastructure as foundational, unglamorous but essential plumbing supporting the broader enterprise generative AI application development wave, since many companies building AI applications on top of their own proprietary document collections have found that reliably extracting and structuring content from often messy, inconsistently formatted real-world document collections represents a surprisingly significant technical challenge that Unstructured's specialized tools aim to address more effectively than building this document processing capability from scratch. The company's customers span enterprises and AI application developers building retrieval-augmented generation and other AI applications that need to process large volumes of unstructured enterprise documents. Unstructured has raised venture funding from investors including Madrona Venture Group and Y Combinator, positioning itself within the growing AI infrastructure and data preparation category.

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