RAGFlow: Build Your Own AI Knowledge Base

Your Documents, Your AI, Your Control

You have hundreds of PDFs, Word documents, and spreadsheets containing everything your business knows. RAGFlow turns that mountain of files into an AI assistant that can answer questions about your data — and show you exactly where it found the answer.

This is called RAG (Retrieval-Augmented Generation), and RAGFlow is one of the best open-source implementations available.

Why RAGFlow Stands Out

Deep document understanding. Most RAG tools just chop documents into chunks and hope for the best. RAGFlow actually understands document structure — tables, headers, lists, images with text. It knows that a number in a table cell means something different than the same number in a paragraph.

Citations built in. Every answer includes a reference to the exact page, paragraph, and document it came from. You can click through and verify. This is essential for professional use where accuracy matters.

Multiple file formats. PDF, Word, Excel, PowerPoint, plain text, markdown, even scanned documents with OCR. Upload whatever you have.

Conversation memory. Ask follow-up questions naturally. "What were our Q3 sales?" followed by "How does that compare to Q2?" RAGFlow remembers context across a conversation.

Real Use Cases

Law firms upload case files, contracts, and legal research. Attorneys ask questions and get answers with specific document citations they can verify and use.

Healthcare organizations build knowledge bases from clinical guidelines, formularies, and policy documents. Staff get instant answers instead of searching through binders.

Engineering teams upload technical documentation, specifications, and design documents. New team members get up to speed in days instead of weeks.

Small businesses centralize their scattered knowledge — employee handbooks, process documents, vendor contracts — into one searchable AI assistant.

Setting It Up

RAGFlow runs as a Docker application on your own server. You need a machine with at least 16GB of RAM and a decent CPU for processing documents.

git clone https://github.com/infiniflow/ragflow.git
cd ragflow/docker
docker compose up -d

Upload your documents through the web interface. RAGFlow processes them automatically, building the knowledge base. Then start asking questions.

The web interface is clean and intuitive. No command-line knowledge needed after the initial setup.

Privacy First

Because RAGFlow runs on your own infrastructure, your documents never leave your control. This matters for legal firms, healthcare organizations, and any business handling sensitive data. No data goes to third-party servers unless you explicitly connect an external AI model.

You can run it entirely with local AI models for complete privacy, or connect it to Claude or GPT for better answer quality.

Find knowledge base and RAG tools on a-gnt