Kotaemon vs RAGFlow
No leader: the top candidate RAGFlow has only 0.09 confidence (low), below the 0.35 needed to declare a winner. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for rag tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Kotaemon
A RAG platform designed for both end users performing document analysis and developers building custom AI-powered QA systems. Offers a web-based interface with support for multiple LLMs, embedding models, and document formats.
RAGFlow
RAGFlow is an open-source RAG engine that streamlines data processing and integration for building production-ready AI systems. It supports multiple data formats and provides configurable LLM and embedding options with agent-based workflows.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- OpenAI
Kotaemon
- AzureOpenAI
- Cohere
- Ollama
- Groq
- VoyageAI
- Docling
- Gradio
- Azure OpenAI
- LanceDB
- GraphRAG
RAGFlow
- Discord
- Feishu
- Telegram
- Line
- Confluence
- S3
- Notion
- Google Drive
- DeepSeek
- Gemini
- OpenClaw
- OpenAI GPT-5
- Google Gemini 3 Pro
- DeepSeek v4
- MCP
Kotaemon or RAGFlow: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.