Unstructured data platform for GenAI that connects to any source, processes 64+ file types, and outputs clean AI-ready inputs.
Unstructured data platform for GenAI that connects to any source, processes 64+ file types, and outputs clean AI-ready inputs.
Unstructured is the most widely deployed open-source document ingestion library, plus a managed platform that productizes the same pipeline for enterprise. It solves the unglamorous but critical first mile of every RAG and agent system: pulling content out of PDFs, slide decks, emails, HTML, images, spreadsheets, and 60+ other file types, normalizing it into typed elements (titles, paragraphs, lists, tables, figures), and emitting clean JSON, Markdown, or chunks ready to embed. The platform's biggest differentiator is the connector library — pre-built source connectors for SharePoint, Google Drive, S3, Salesforce, Confluence, Slack, and dozens more, and destination connectors that write into Pinecone, Weaviate, OpenSearch, Postgres pgvector, and other vector stores. That means a team can wire "every PDF in a SharePoint site, refreshed nightly, into a vector index" without building a custom ETL. Unstructured also exposes a serverless API for ad-hoc parsing, and the underlying library remains open source under Apache 2.0 with hundreds of thousands of downloads per month. Pricing is metered per page processed plus connector fees on the enterprise platform. Best fit for AI engineering teams that have validated a RAG prototype and need a production-grade ingestion pipeline they will not have to rebuild every quarter.
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Unstructured is the most comprehensive document processing pipeline, handling virtually every document format and producing clean, structured output suitable for RAG systems. The open-source library works well for common formats, while the managed API adds OCR, table extraction, and high-volume processing. Users note that output quality varies significantly by document type and complexity — simple text documents work perfectly, while complex PDFs with tables and images require more tuning. The API pricing can be significant at scale.
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