ragflow vs ken
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.; ken: Ken is a pure Go port of semble, providing fast hybrid code search for agents with drop-in MCP compatibility. It offers a single static binary distribution, approximately 44x fewer tokens than grep+Read at recall@10, and supports indexing source code and documentation. The retrieval algorithm is a verbatim port of semble's hybrid BM25 + Model2Vec approach.
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.
Agent code search: quickly find relevant code chunks across large codebases
Side-by-Side Comparison
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