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Unstructured

Unstructured is a data preprocessing platform for RAG and AI agents that converts PDFs, scans, tables, forms, and more than 50 file types into clean, structured, agent-ready data. By automatically matching processing strategies, it parses complex tables, uses OCR to recognize scanned documents and handwritten content, understands the layout and reading order of multi-column PDFs, and supports cleaning, chunking, and embedding results before writing them to vector databases. Users can invoke the Unstructured Transform service via API or MCP, or connect to more than 20 data sources such as S3, SharePoint, Drive, Snowflake, and Databricks, and output to more than 20 destinations. The platform complies with SOC 2 Type 2, HIPAA, GDPR, ISO 27001, FedRAMP High, and other compliance requirements, and can be deployed in shared SaaS, isolated instances, or its own VPC, serving document intelligence scenarios in industries such as finance, healthcare, the public sector, legal, manufacturing, and insurance.

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About this tool

Unstructured is committed to transforming unstructured data into structured data for use by RAG and AI agents. According to the official introduction, it can process PDFs, scans, spreadsheets, and more than 50 file types, outputting clean, structured data that agents can trust. Its core processing philosophy is "Point. Parse. Done." — every file is different, and Unstructured knows how to handle each one and automatically applies the correct processing strategy without manual setup.

Main capabilities include:

  • Table extraction: preserves rows, columns, headers, and relationships, maintaining structure even for complex tables spanning multiple pages.
  • OCR: captures text with high accuracy from scans, images, handwritten content, and low-quality documents.
  • Complex layout understanding: preserves reading order, hierarchy, sections, and relationships between pages, so extracted content remains faithful to the original.
  • Multi-format support: PDF is just one of more than 50 file types, also covering Word, Excel, PowerPoint, email, HTML, images, and scans, all processed through the same pipeline.
  • Data connectivity: can connect to more than 20 data sources (S3, SharePoint, Drive, Snowflake, Databricks, etc.) and write to more than 20 destinations, including major vector databases, without writing glue code.
  • Complete pipeline: not only parses files, but also handles connecting sources, chunking, embedding, and loading into databases at scale on a schedule.

How to use: Unstructured provides Unstructured Transform, available via API or MCP, and the official description says "start for free." Users can "install Unstructured in minutes" to turn any file into structured, agent-ready data. Installation and invocation details are provided in the official documentation; the current materials do not give the specific command content.

Applicable scenarios by industry include:

  • Financial institutions: turn financial reports, regulatory documents, and risk summaries into structured data pipelines to meet compliance and speed requirements.
  • Healthcare and life sciences: turn complex documents such as trial protocols, academic reports, and insurance forms into structured, GenAI-ready data.
  • Public sector: turn regulatory documents, procurement records, and voter forms into structured pipelines oriented toward transparency and scale.
  • Legal teams: extract structure and insights from dense documents, contracts, and disclosure materials, making it easy to use GenAI for search, analysis, and review.
  • Manufacturing: turn dense technical documents such as technical manuals, engineering drawings, and supplier specificationsConvert into structured, searchable data.
  • Insurance industry: Convert form-heavy, handwritten, and scanned documents such as ACORD forms, policy contracts, and claims documents into structured data to accelerate underwriting and claims.

Typical users and cases: SAP, IBM, Intel, Teradata, and Uniphore use Unstructured to convert complex documents into production-grade AI data.

Enterprise-grade deployment and compliance: Unstructured can be deployed in the cloud or in private environments, ready to use out of the box or deeply customized. It complies with standards such as SOC 2 Type 2, HIPAA, GDPR, ISO 01, and FedRAMP High, and can run in shared Business SaaS, dedicated isolated instances, or fully deployed in the user's own VPC.

The official FAQ also explains the product positioning:

  • Why not just have the model read PDFs directly? For a single clean file it is fine, but when facing thousands of constantly changing messy documents, the model consumes a large number of tokens and gets entangled with layout; Unstructured first cleans and structures them, thereby obtaining better answers at lower cost.
  • It is not just a PDF parser, but a unified pipeline covering more than 50 file types.
  • Parsing is only the simple part; the real value lies in connecting data sources, chunking, embedding, and loading into databases at scale on a schedule.
  • It supports pulling directly from S3 or SharePoint and writing to vector databases, with no glue code required.
  • Built for regulated data, it supports multiple compliance certifications and deployment methods.

Limitations and information not provided: The current materials do not provide specific pricing plans, free tier details, installation commands, API endpoint formats, performance benchmarks, or comparison data with other tools. To contact support, you can send an email to support@unstructured.io, or schedule a call to learn more.

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