Chat with your own documents: AnythingLLM, from Mintplex Labs, wraps retrieval-augmented generation (RAG) in an open-source application anyone can run. You organize content into workspaces, each an isolated namespace with its own documents, vector embeddings, chat history, and settings, so one instance can hold several separate knowledge bases. Upload PDFs, DOCX, TXT, and other formats, or scrape web pages; the built-in collector parses and chunks them into a vector database (LanceDB by default, with Pinecone, Chroma, Qdrant, and others supported). Answers cite their source documents. It works with both cloud LLMs (OpenAI, Anthropic, Gemini) and local ones via Ollama or LM Studio, and the embedding model is separately configurable. Beyond RAG chat, it includes AI agents that can browse the web and run tools, an embeddable chat widget for your website, a developer API, and multi-user mode with admin, manager, and default roles plus per-workspace access control. Context assembly is smarter than naive RAG: pinned documents, attached files, vector search hits, and recent chat history are combined under a token budget so the model's context window is filled efficiently, and each workspace supports multiple independent conversation threads against the same knowledge base. Because the embedding model, vector store, and chat LLM are all independently swappable, you can move between providers without re-ingesting a single document. The stack is Node.js with a React frontend, MIT-licensed.

With 6,800 GitHub stars and over a decade of development since its 2014 release, ONLYOFFICE Docs delivers a self-hosted Microsoft Office replacement with pixel-perfect OOXML rendering and real-time collaborative editing supporting both Fast (character-by-character) and Strict (manual save) co-authoring modes. The suite encompasses five full-featured editors — Document Editor for DOCX/ODT/EPUB/HTML, Spreadsheet Editor with 500+ functions and pivot tables, Presentation Editor with animations and transitions, Form Creator for fillable PDF forms with field validation, and PDF Editor for annotation and conversion — all operating within a unified web interface. Format support spans 50+ types including DOCX, XLSX, PPTX, ODT, ODS, ODP, PDF, CSV, RTF, TXT, and Markdown with server-side conversion between any supported pair. The JavaScript plugin API enables extending editor functionality through a marketplace of ready-made plugins for ChatGPT integration, speech-to-text, OCR, Zotero citations, and Thesaurus. Ready-to-use connectors integrate with Nextcloud, ownCloud, Seafile, Moodle, Odoo, Confluence, SharePoint, Alfresco, Liferay, and Chamilo, while WOPI protocol compliance enables integration with any WOPI-compatible platform. JWT authentication secures all API communications between host applications and the document server. Deploy via Docker with a single command or DEB/RPM packages on Ubuntu, Debian, CentOS, or RHEL. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPL v3 licensed.

Merge, split, compress, convert, edit, annotate, redact, OCR, and sign PDFs - BentoPDF packs over 130 tools into a privacy-first toolkit that runs entirely in the browser through WebAssembly. Files are never uploaded - processing happens in browser memory on the user's machine and disappears when the tab closes, which makes the tool GDPR-clean by architecture and safe for financial, legal, and internal documents. The engine combines WASM builds of PyMuPDF, Ghostscript, and CoherentPDF; Tesseract handles OCR with searchable text-layer output; Office conversions cover Word, Excel, and PowerPoint; and digital signatures use X.509 certificates (PFX/PEM) with the private key staying on the client. Because there is no server-side processing, deployment is a static-file exercise: a single Docker container, or any static host. A dedicated self-hosted build strips the marketing pages while keeping every tool, and air-gapped deployments are first-class - an automated script bundles the WASM modules, OCR language data, and fonts for fully offline networks. No accounts, no limits, no watermarks; TypeScript and Vite under the hood.

A pile of paper becomes a searchable digital archive under Paperless-ngx, the community-maintained document management system. The pipeline is what makes it work: drop a file into the consumption folder (or let it poll an email inbox), and a worker hashes it for duplicate detection, routes it by type, runs OCRmyPDF with Tesseract (100+ languages) on anything without a text layer, and produces an archivable PDF/A with invisible selectable text embedded - so Ctrl+F works on your scans. Then the smart part: a scikit-learn classifier (TF-IDF plus multi-label prediction) trained on your own tagged documents automatically assigns tags, correspondents, and document types to new arrivals, alongside rule-based exact, keyword, and regex matching for deterministic cases. Full-text search includes relevance ranking, match highlighting, autocomplete, and "more like this" similarity search. Apache Tika integration extends consumption to Word, Excel, PowerPoint, and LibreOffice formats. The Django/Angular app adds custom fields, saved views on a customizable dashboard, bulk editing, workflow automation triggered on upload or matching, shareable public links with expiration, and a robust permissions system with per-document access control. Metadata lives in PostgreSQL with Redis-queued Celery workers processing documents in parallel. Your tax records, invoices, and contracts stay on your server - searchable in seconds, never in someone else's cloud.

Adobe Acrobat and Smallpdf, answered by a self-hosted Java web application: Stirling PDF processes every file with its 60+ tools on your own server and deletes it after the task completes. Nothing is uploaded to a third party, which is the whole point for contracts, invoices, and medical records. The toolbox covers page operations (merge, split at page numbers or scanned dividers, rotate, reorder, crop, extract), conversion in both directions between PDF and Word, Excel, PowerPoint, images, HTML, and Markdown, OCR that turns scans into searchable PDFs via Tesseract/OCRmyPDF (including PDF/A archival conversion), and security tools for passwords, permissions, watermarks, signatures, and true UI-driven text redaction. A built-in viewer handles annotation, drawing, and text or image insertion, and V2 added stateful processing - upload once, chain multiple tools - plus undo/redo history. For automation, nearly every tool has a REST API endpoint, no-code pipelines combine operations into custom logic chains, and watched folders process files automatically. Enterprise deployments get SSO, user management, and audit logging; the interface ships in 40+ languages. With 84K+ GitHub stars it is the most popular PDF tool in self-hosting, replacing $20/month Acrobat subscriptions with flat infrastructure cost.

RAGFlow has established itself as one of the most widely adopted open-source RAG engines available, powering production AI systems that demand traceable, hallucination-free answers from complex enterprise data. The platform processes PDF, DOCX, Excel, and PPT files through vision-based deep document understanding with layout analysis and OCR, extracting structured knowledge from tables, charts, and images that simpler parsers miss entirely. RAGFlow's hybrid retrieval pipeline combines vector search with BM25 keyword matching and multi-stage reranking across configurable document stores including Elasticsearch, InfiniFlow's Infinity engine, OpenSearch, and OceanBase. Developers connect any combination of LLM providers — OpenAI, DeepSeek, Anthropic Claude, Google Gemini, and locally-hosted models via Ollama — through a unified configuration layer. The visual agent workflow system enables multi-step reasoning chains with persistent memory, tool calling, and pre-built templates for common enterprise scenarios. RAGFlow synchronizes data from Confluence, S3, Notion, and Google Drive, and delivers answers through chat integrations with Feishu, Discord, Telegram, and Line. The Python SDK and RESTful API on port 9380 provide programmatic access to knowledge base management, document parsing, and conversational retrieval. The full stack deploys via Docker Compose with MySQL for metadata, Redis for task orchestration, and MinIO for object storage. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Kotaemon is a document QA platform that combines advanced RAG techniques with a clean Gradio-based web interface for chatting with your documents. Built by Cinnamon, the Python backend supports any LLM provider including OpenAI, Azure OpenAI, Cohere, Groq, and local models via Ollama and llama-cpp-python, with a model management panel for configuring LLM and embedding providers from the UI. The default hybrid RAG pipeline combines full-text keyword retrieval with vector similarity search and applies re-ranking to ensure optimal result quality, while multi-modal document parsing extracts content from tables and figures alongside text. Advanced citations link every answer to specific source passages with relevance scores, viewable directly in the built-in PDF viewer with highlighted text spans. GraphRAG indexing via NanoGraphRAG, LightRAG, or Microsoft GraphRAG builds knowledge graphs from document collections for relationship-aware retrieval. Agent-based reasoning supports question decomposition for multi-hop queries using ReAct and ReWOO strategies. Multi-user authentication organizes documents into private and public collections with sharing and collaboration features. The platform supports Docker deployment in lite, full, and Ollama-bundled variants, runs on port 7860, and stores application data in a persistent volume. MCP tool integration enables external system connections for extended retrieval capabilities. On RepoCloud, deploy Kotaemon on a dedicated VPS with Docker, root SSH access, and complete control over your document AI infrastructure, all under the Apache 2.0 license.

Mayan EDMS stores, classifies, and retrieves millions of documents with automatic OCR, workflow automation, and audit-ready access controls that organizations have relied on for over a decade. Tesseract integration extracts searchable text from scanned PDFs and images in over 100 languages, transforming paper archives into instantly queryable digital collections without manual data entry. The workflow engine routes documents through approval chains using configurable state machines that trigger notifications, enforce retention policies, and maintain complete audit trails for regulatory compliance. Version tracking preserves every revision with full diff capabilities, while GnuPG digital signatures provide cryptographic proof of authenticity and tamper detection for sensitive records. Role-based permissions combined with object-level ACLs and LDAP integration ensure documents remain visible only to authorized users, down to individual file granularity. Full-text search powered by Whoosh or ElasticSearch handles advanced queries across massive document stores with faceted filtering and relevance ranking. The Django REST Framework API enables programmatic upload, metadata extraction, and workflow triggering from external systems. Beyond simple folder hierarchies, metadata schemas, document types, tags, and cabinet structures provide multi-dimensional classification tailored to how your organization actually works. Background processing through Celery handles OCR, conversion, and preview generation asynchronously, keeping the web interface responsive under heavy ingest loads.