Unstructured iconUnstructured

open-source Freemium Star14k

Unstructured is an open-source and commercial ETL platform that converts 64+ file types into structured, AI-ready data for LLM and RAG pipelines, trusted by 87% of Fortune 1000 companies with SOC 2 Type II, HIPAA, and FedRAMP High compliance.

64+ File Types
87% Fortune 1000
14.9K GitHub Stars
15K Free Pages

Overview

Unstructured is the enterprise standard for unstructured data ETL — connecting to any document source, processing 64+ file types, and delivering clean, chunked, enriched data ready for LLM and RAG pipelines. Available as a self-hostable open-source library and a fully managed cloud platform, it serves both individual developers and Fortune 1000 enterprises including McKinsey, JPMorgan Chase, Google, Amazon, and Citibank. Its $0.03/page pay-as-you-go pricing, 30+ source connectors, 1,250+ pre-built pipelines, and full compliance stack (SOC 2 Type II, HIPAA, GDPR, FedRAMP High, ISO 27001) make it the widest-reaching and most enterprise-ready option in the document ingestion space. Founded in 2022 by Brian S. Raymond (formerly CIA/PrimerAI), Unstructured has earned recognition from CB Insights AI 100, Forbes Top 50 AI Companies, and Gartner Cool Vendor.

The Verdict

Who Should Use Unstructured?

Best For

  • Enterprises with compliance requirements — SOC 2, HIPAA, FedRAMP High, GDPR, ISO 27001 all covered
  • Pipelines ingesting diverse file types — 64+ formats including email, HTML, Office, images, and PDFs
  • Teams using LangChain, LlamaIndex, Haystack, or major vector databases — native connectors available
  • Organizations needing a no-code UI AND a developer API from the same platform
  • Government and regulated industries requiring FedRAMP High certification

Not Ideal For

  • Complex table extraction — only 75% accuracy on complex tables vs. Docling's 97.9%
  • Speed-sensitive pipelines — slowest major option at ~141 seconds for 50 pages vs. LlamaParse's ~6 seconds
  • Cost-minimizing self-hosted workloads — Docling is free and faster locally
  • Simple, fast PDF parsing where a lighter tool would do

What's Great

  • Widest file type coverage — 64+ formats including email (EML, MSG), HTML, Office, images, and PDFs
  • Full enterprise compliance stack — SOC 2 Type II, HIPAA, GDPR, FedRAMP High, ISO 27001
  • Trusted by 87% of Fortune 1000 — McKinsey, JPMorgan, Google, Amazon, Citibank among named customers
  • 30+ source connectors and 1,250+ pre-built pipelines — fastest path to production for complex data estates
  • 100% accuracy on simple table extraction in independent benchmarks
  • Generous free tier — 15,000 pages with no expiration
  • Self-hosted open-source library available alongside managed cloud
  • #1 content fidelity on own benchmark vs. LlamaParse VLM (0.880 vs 0.835 Adjusted CCT)

Watch Out For

  • Slowest processing speed — 51 seconds for 1 page, 141 seconds for 50 pages vs. LlamaParse's consistent ~6 seconds
  • Only 75% accuracy on complex tables — severe column shift errors in complex nested structures
  • Fails to reconstruct table of contents properly — captures headers but omits entries
  • Business pricing requires a sales contact — no self-serve enterprise plan
  • Heavy Python dependency stack — large container size and complex installation
  • Benchmark data is primarily self-reported via Unstructured's own SCORE framework

Pricing

View all features & details

Supported File Types (64+)

  • PDF (scanned + digital, with OCR)
  • DOCX, PPTX, XLSX (Office documents)
  • HTML, RST, RTF, ODT, EPUB
  • PNG, TIFF, JPEG, BMP (images)
  • EML, MSG (email)
  • Plain text, CSV, XML, JSON
  • Markdown, LaTeX

Processing Pipeline

  • Intelligent partitioning (layout-aware)
  • VLM partitioner for complex visual layouts
  • Contextual chunking strategies
  • Enrichment (metadata, entity extraction)
  • Embedding generation
  • Built-in OCR for scanned documents

Integrations

  • LLM Frameworks: LangChain, LlamaIndex, Haystack
  • Vector DBs: Weaviate, Pinecone, Redis, Elasticsearch, Neo4j, AstraDB, MongoDB
  • Data annotation: Label Studio, LabelBox, Argilla, Prodigy, Datasaur
  • Data tools: Pandas, Hugging Face Transformers
  • Sources: S3, SharePoint, and 30+ more connectors

Compliance & Security

  • SOC 2 Type II certified
  • HIPAA compliant
  • GDPR compliant
  • FedRAMP High certified
  • ISO 27001 certified
  • Role-based access controls (Business tier)
  • Full data isolation via dedicated VPC

Deployment Options

  • Open-source Python library (self-hosted)
  • Managed cloud API
  • Dedicated instance (Business)
  • VPC deployment (Business)
  • No-code UI + developer API (dual interface)

Awards & Recognition

  • CB Insights AI 100 (2024)
  • Forbes Top 50 AI Companies
  • Fast Company #24 Most Innovative (2025)
  • Gartner Cool Vendor (2024)

How It Compares

Feature Unstructured Docling LlamaParse
File Types 64+ 20+ 130+
Simple Table Accuracy 100% 97.9% 100%
Complex Table Accuracy 75% 97.9% Inconsistent
Processing Speed (50 pages) 141s 65s ~6s (cloud)
Self-hosted Yes Yes No
Enterprise Compliance SOC2, HIPAA, FedRAMP None None
Source Connectors 30+ None None
Pre-built Pipelines 1,250+ None None
Pricing Free / $0.03/page Free (MIT) $0.0013–$0.056/page
Best For Compliance + breadth Accuracy + privacy Speed + complex PDFs

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