ragflow vs rtfm
ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that integrates RAG with Agent capabilities. It provides a superior context layer for LLMs and offers a streamlined RAG workflow adaptable to enterprises of any scale.; rtfm: RTFM is a local, open-source retrieval layer that indexes everything in a project (code, docs, PDFs, etc.) so that AI agents can find the right context instantly without hallucinations or cloud costs. It integrates with Claude Code and other MCP clients, supports multiple formats, and provides fast search with progressive disclosure.
TL;DR
- Your documents have complex layouts (PDFs, scanned files, tables, slides) and you need layout analysis, OCR, and traceable citations.
- You want an Apache-2.0 all-in-one RAG platform where you can inspect and hand-tune template-based chunks in a web UI.
- Your server has less than 4 CPU cores and 16 GB RAM; RAGFlow's multi-service stack is heavy.
- You want an autonomous web research agent that writes 2,000-word reports from live search rather than indexing a local document corpus; GPT Researcher fits better.
Legal and regulatory document retrieval with support for specialized formats
Side-by-Side Comparison
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