Unstructured
Unstructured is an ETL platform provider for transforming unstructured data into LLM-ready formats through open-source libraries and enterprise APIs supporting 25+ file types with 50+ source and destination connectors.
Overview
Unstructured provides an automated ETL solution for document processing that extracts and transforms data from PDFs, images, HTML, Word documents, emails, scanned documents, and handwritten notes. The platform offers three transformation tiers: Basic for text-only documents, Advanced for PDFs and complex files, and Platinum with VLM API integration for scanned and handwritten content. Unstructured includes a no-code drag-and-drop Workflow Builder alongside API access for engineers. Founded in 2022 by Brian Raymond, Matt Robinson, and Crag Wolfe after working together at Primer AI, the company raised $65M from Bain Capital Ventures, Menlo Ventures, Madrona Venture Group, M12, and MongoDB Ventures.
Key Features
- 25+ File Type Support: Processes PDFs, images, HTML, Word, emails, scanned documents, handwritten notes
- Three Transformation Tiers: Basic (text-only), Advanced (complex PDFs/images), Platinum (VLM API for scanned/handwritten)
- 50+ Connectors: Source and destination connectors with automatic new data detection
- Workflow Builder: No-code drag-and-drop ETL orchestration for chunking, embeddings, and vector store mapping
- Partitioning: Extracts structured content from raw unstructured documents
- Cleaning and Chunking: Data preparation and segmentation for LLM consumption
- API and UI: Both user interface for teams and API for engineering control
- Auto-Scaling: Horizontal scaling with 300x concurrency per organization
- Weekly Model Updates: Regular addition of image-to-text, text-to-text, text-to-embedding models
Use Cases
GenAI Data Preparation
Organizations preparing data for large language models use Unstructured to transform documents from multiple sources into LLM-ready formats. The platform automatically detects new files from 50+ connectors, applies appropriate transformation tiers based on document complexity, and delivers structured outputs to vector databases for RAG workflows.
Enterprise Document ETL
Enterprises deploy Unstructured for continuous extraction from diverse document repositories. The Workflow Builder orchestrates multi-step transformations including partitioning, cleaning, chunking, and embedding generation without code, with RBAC controls and in-VPC deployment for sensitive data.
Scanned Document Processing
Organizations with scanned and handwritten documents use the Platinum tier with VLM API integration. The platform processes challenging document types including low-quality scans and handwritten notes, applies appropriate cleaning and chunking, and delivers structured data to downstream AI systems.
Technical Specifications
| Feature | Specification |
|---|---|
| Platform Types | Open-source library, Enterprise UI, Enterprise API |
| File Types | 25+ including PDFs, images, HTML, Word, emails, scanned/handwritten |
| Transformation Tiers | Basic (text-only), Advanced (complex), Platinum (VLM API) |
| Connectors | 50+ source and destination |
| Processing | Partitioning, cleaning, extraction, chunking, embeddings |
| Workflow | Drag-and-drop no-code builder |
| Concurrency | 300x per organization |
| Scaling | Horizontal auto-scaling |
| Deployment | Cloud, in-VPC |
| Compliance | SOC 2 Type 2, HIPAA, GDPR |
| Access Control | RBAC, granular admin controls |
| Model Updates | Weekly additions (image-to-text, text-to-text, text-to-embedding) |
Resources
Company Information
Headquarters: Rocklin, California, United States
Founded: 2022
Founders: Brian Raymond (CEO), Matt Robinson, Crag Wolfe
Employees: ~40
Funding: $65M ($40M Series B March 2024, from Bain Capital Ventures, Menlo Ventures, Madrona Venture Group, M12 - Microsoft's Venture Fund, Mango Capital, MongoDB Ventures, Shield Capital)
Previous Experience: Founders worked together at Primer AI and CIA
