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.

Convert paper archives, email attachments, and PDF records into an organized digital repository with Docspell, an open-source document management system that automates optical character recognition, metadata extraction, and full-text search. Users can ingest receipts and invoices through network scanners, monitored IMAP email mailboxes, mobile uploads, or drag-and-drop browser tools. The background processing pipeline executes optical character recognition via Tesseract, enhances image contrast with unpaper, and extracts text from Word documents and PDFs. Machine learning algorithms analyze document syntax to predict correspondents, suggest relevant organization tags, and identify due dates automatically. Team members can search their entire filing cabinet using complex Boolean queries and full-text indexing powered by Apache Solr or PostgreSQL. Administrators can configure multi-user collectives with isolated permissions, define custom metadata attributes, set up webhooks, and share time-limited document download links. Users can also merge multi-page scans, track processing job queues, and export curated document collections for tax filings or legal audits. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPL v3.0 licensed.

Somewhere between the shoebox and the inbox, Papra keeps receipts, warranties, and leases in a self-hosted archive you can actually search. Upload a photographed receipt and built-in OCR reads its text, so a search for the store name finds it later. Searches combine name:, content:, tag:, created:, and has: filters with AND, OR, NOT, and parentheses, and any query can be saved as a sidebar view. Tagging rules label uploads by name or content and can be applied to documents already stored. Optional AI auto-tagging works with a cloud provider or a local model such as Ollama. Custom properties add searchable typed fields such as text, number, date, yes or no, and select. Organizations keep a household's or a team's archive apart, with owner, admin, and member roles. Share links let outsiders open a document without an account, with optional passwords and expiry dates, and each link can be switched off. Forward an email to a generated address, or drop files into a watched folder, and documents arrive without opening the app; both are opt-in. Deleted files wait 30 days in the trash, and optional encryption protects stored files. Sign in with email, GitHub, Google, or a custom OAuth2 provider, and script the archive through the API, SDK, CLI, or webhooks. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Receipts, contracts, and letters that arrive as pixels rather than text: Papermerge is a document management system built specifically for scanned documents. Upload a PDF, TIFF, JPEG, or PNG and OCR runs automatically, with a real-time status indicator beside the document title; under the hood it drives OCRmyPDF and Tesseract, supporting 130+ languages and producing a new document version with a selectable, searchable text layer you can download. Full-text search runs across everything, with multiple search-engine backends (Xapian by default). The interface deliberately mimics a modern desktop file browser: dual-panel commander, drag and drop, hierarchical folders, and colored tags on documents and folders. Page management fixes what scanners get wrong - delete blank pages, rotate, reorder, merge, extract, and move strayed pages between documents, powered by PikePDF. Document types act as categories, each with its own custom metadata fields, so invoices carry vendor and amount while contracts carry parties and dates. Versioning preserves every state of a document. Multi-user support includes groups, group ownership, permission management, and document/folder sharing between users and groups, and an OpenAPI-compliant REST API automates ingestion from scanners or scripts. Apache-licensed, ideal for long-term digital archives.

Every scan and PDF you drop into Teedy becomes searchable text in a self-hosted document archive, filed by nested tags instead of folders. OCR reads images in more than twenty languages, and the search box offers suggestions and highlights matches, even inside ODT, DOCX, and PPTX files. Video files are supported as well. Each record carries Dublin Core fields plus custom metadata of your own design, with comments and earlier file versions attached. When a document needs a second pair of eyes, workflow steps with assigned reviewers move it along in order until someone signs off. Pull in EML emails, let the server poll an inbox, or point the bulk importer at a whole folder, and incoming paperwork needs no manual filing. Share a single document through a public link, or keep it behind user and group permissions with a storage quota for each person. LDAP and two-factor authentication guard sign-in, 256-bit AES encryption protects stored files, and an audit log records who changed what. Webhooks alert other services, a documented REST API lets scripts take part, and an Android client carries the archive on a phone. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-2.0 licensed.

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.

LogicalDOC is a document management system that gives a company one controlled home for its files instead of letting contracts, invoices, and procedures scatter across drives and inboxes. Staff store any kind of document in a repository organized on multiple levels, then find it again through advanced search that reaches inside document content, not just filenames. Colleagues collaborate on the same documents and projects while version control keeps the history straight, so nobody works from last quarter's draft by accident. Administrators define roles for different users, set access control and user quotas, and choose the security level for each area, with detailed activity logs showing who opened, changed, or shared what. Automations handle the routine flow of documents through the business, and the web services API lets an ERP or other systems integrate document management into existing processes. Information can be collected from any digital source, knowledge gets reused instead of recreated, and mobile apps for phones and tablets keep the repository reachable away from the desk. The official Docker image and Tomcat bundles make the Community Edition straightforward to run on your own infrastructure. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. LGPL-3.0 licensed.

Small businesses file every invoice, contract, and letter by what it is instead of by folder with SimpleDMS, a document management system built around types, tags, and searchable metadata. Upload a document to the inbox, pick its type, and the sidebar offers exactly the tags and fields that type needs, so an incoming invoice asks for the issuing company and receipt date instead of a blank properties page. Name-giving attributes label each file automatically from its own metadata, and the Browse view finds it again by company, date, or approver in seconds. Spaces act as workspaces with their own document types, tags, and permissions, so the team shares project files in one space, exchanges papers with an accountant or customers in another, and keeps private records apart. Tag groups such as companies and employees stay consistent across thousands of documents, date and text fields capture the facts you search by later, and values can be corrected at any time when a document was filed in haste. Dark mode is built in, the interface runs comfortably on a tablet at the scanner, and no analytics or tracking watch how your office works. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Docling Studio shows you exactly what a document parser sees, drawing a colored box around every title, paragraph, table, and picture it extracts from your PDFs. Import a PDF, run an analysis, and the result opens with three linked panels: the document tree on the left, the paged preview in the center, and the selected element on the right with its type, page, position, and text or table. Click any box on the page and the same element lights up in the tree and properties panel as other boxes fade away. The layers bar counts each element type and toggles boxes per type, or hides them all to reveal the bare page. You can analyze several documents at once from the list, watch progress percentages on long files, and queue work three analyses at a time. Ask a question and a local model answers from the document, with a reasoning timeline that links each step back to the passage it read. Finished results download as the original PDF, clean Markdown, or Docling JSON for downstream pipelines. AI agents connect over MCP to read and cite your documents, and an optional connection to your own Docling Serve server handles heavier parsing loads. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Messy PDFs, slide decks, spreadsheets, and web pages become clean, structured text for AI pipelines once Docling Serve has converted them. Open the built-in playground, paste a link or drop a file, and press Convert to see the result beside the options that produced it. A page viewer draws the detected layout over each scanned page, with filters for text, tables, and pictures. Output tabs show Markdown, HTML, and JSON, and one click downloads everything as a zip. The options panel picks OCR engines, table structure models, picture descriptions, code and formula enrichment, and chart extraction, each with its own preset. Copy the exact request as a curl command or a Python snippet and move it straight into production code. A Server tab lists the limits, supported sources and targets, installed library versions, and every model preset the instance offers. Optional API keys, S3 or Google Drive sources, and async task queues cover shared team deployments. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

See exactly what your documents look like before a retrieval pipeline swallows them. Chunky puts the original PDF next to the converted Markdown with page-aware scrolling, so broken tables, scrambled columns, and stray artifacts are visible at a glance. Pick a converter, edit the Markdown by hand, then split it into color-coded chunks you can edit, delete, or enrich one at a time. Compare two converters on the same pages in a side-by-side dialog to find which one handles your layouts best. Try token, recursive, sentence, semantic, table, code, and heading-based splitters with adjustable size and overlap, and save the chunk sets that work. Optional model-powered enrichment adds titles, one-sentence context, summaries, keywords, and retrieval questions to each chunk. Process many documents in one batch and export everything as a ZIP. Judge chunk quality by eye, not by guesswork, before any of it reaches an embedding model. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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.

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.

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.

Years of bank statements, pay stubs and receipts sit scattered across dozens of websites, each demanding a login and offering one PDF at a time. PaperPull fetches that whole history for you: sign in yourself in a real browser window, answer the two-factor prompt, and it downloads statements, receipts, pay statements, W-2s and tax forms from 73 supported providers including Chase, Amex, ADP, Amazon, Walmart, Vanguard and Verizon. The tool only ever downloads; it never pays a bill, moves money or changes a setting, and that read-only promise is enforced by construction rather than by policy. Every archive is checked for freshness and for holes in the middle, so a series that looks current but quietly skipped three months is flagged by name, with per-account cadence learned from your own documents. Receipts become one long spreadsheet of every item you have ever bought across every store, with prices and dates, while transactions are read out of statement PDFs into workbook rows that are verified against each statement's printed beginning and ending balances. New documents can flow straight into a Paperless-ngx consume folder, everything runs under a password you choose on your own network, and no cloud account is involved anywhere. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 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.