Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.

Get your documents ready for gen AI

Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.

PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.

Knowledge Agents and Management in the Cloud

ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows.

Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.

OpenOCR: An Open-Source Toolkit for General-OCR Research and Applications, integrates a unified training and evaluation benchmark, commercial-grade OCR and Document Parsing systems, and faithful reproductions of the core implementations from a wide range of academic papers.

Eden AI: simplify the use and deployment of AI technologies by providing a unique API that connects to the best possible AI engines

Open-source spreadsheets platform for deep research and document processing

Hybrid RAG system combining vector search, knowledge graph (LightRAG), and cross-encoder reranking — with Docling document parsing, visual intelligence (image/table captioning), agentic streaming chat, and inline citations. Powered by Gemini or local Ollama models.

A comprehensive list of document parsers, covering PDF-to-text conversion and layout extraction. Each tested for support of tables, equations, handwriting, two-column layouts, and multi-column layouts.

MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations.

Jupyter notebooks testing different OCR models for document parsing (Dolphin, MonkeyOCR, Marker, Nanonets, ...)

A Unified Toolkit for Deep Learning-Based Table Extraction

A Python pipeline tool and plugin ecosystem for processing technical documents. Process papers from arXiv, SemanticScholar, PDF, with GROBID, LangChain, listen as podcast. Customize your own pipelines.

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

Docling4j brings the functionalities of Docling in document understanding to Java® projects

Official Implementation of "Visual-ERM: Reward Modeling for Visual Equivalence"

Document Filters is an SDK for applications like content indexing, e-discovery, data migration, and feeding data into AI/ML models by extracting data from unstructured sources. It gives the ability to perform deep inspection, data extraction, output manipulation, and conversion for virtually any type of document, in any programming language.