DeepSearcher vs RAGFlow

DeepSearcher

RAG

RAGFlow

RAG

Tagline

DeepSearcher

Open-source agentic RAG framework for private enterprise data, built by the Zilliz/Milvus team.

RAGFlow

Open-source RAG engine with deep document parsing, hybrid search, and visual agent orchestration.

Pricing

DeepSearcher

Free· Free, Apache 2.0; bring your own LLM and vector DB costs

RAGFlow

Freemium· Free tier; Starter $29/mo; Pro $129/mo; Enterprise custom

Free trial

DeepSearcher

Yes

RAGFlow

Yes

API

DeepSearcher

Not listed

RAGFlow

Yes

Platforms

DeepSearcher

cli

RAGFlow

api

Open source

DeepSearcher

Yes

RAGFlow

Yes · Apache-2.0

GitHub stars

DeepSearcher

—

RAGFlow

91,511

checked 2026-09-29

Last GitHub push

DeepSearcher

—

RAGFlow

2026-09-29

First commit

DeepSearcher

—

RAGFlow

2023-12

Model used

DeepSearcher

Multi-model (DeepSeek, OpenAI o1/o3-mini, Claude, Llama, others)

RAGFlow

Multi-model

Best for

DeepSearcher

Pick DeepSearcher if you want an open-source, agentic RAG layer over private data and you are comfortable wiring it to your own LLM and vector database.

RAGFlow

Pick RAGFlow if you need a self-hostable, citation-grounded RAG stack that can actually digest gnarly enterprise documents and feed agents.

Not for

DeepSearcher

Skip it if you want a no-code hosted RAG SaaS, a polished UI, or a turnkey chatbot without writing Python.

RAGFlow

Skip it if you just want a hosted chat-with-PDF widget or you're allergic to running your own infrastructure.

Editorial score

DeepSearcher

6.9 / 10

RAGFlow

8.1 / 10

Use cases

DeepSearcher

enterprise-ragagentic-searchprivate-document-qaresearch-agentsknowledge-base-search

RAGFlow

document-qaenterprise-searchagent-orchestrationknowledge-basehybrid-retrieval

Pros

DeepSearcher

• Apache 2.0, fully self-hostable for private data
• Agentic multi-step retrieval, not just one-shot RAG
• Pluggable LLMs and vector stores including Milvus
• Backed by Zilliz, the team behind Milvus

RAGFlow

• Strong deep-document parsing for messy PDFs, tables, and scans
• Hybrid vector + BM25 retrieval with citation-grounded answers
• Fully open-source with active GitHub repo and self-host option
• Visual agent builder plus MCP integration for tool-calling clients
• Model-agnostic; works with most major LLM providers

Cons

DeepSearcher

• Library/CLI, no hosted product or managed API
• Web crawling and some loaders still in development
• Requires engineering effort to deploy and tune
• Best experience assumes you already run Milvus/Zilliz

RAGFlow

• Free tier blocks API access, pushing real use to paid plans
• Self-hosting is non-trivial and resource-hungry
• Documentation and UI lag behind the engine's capabilities

Website

DeepSearcher

zilliztech.github.io

RAGFlow

ragflow.io

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.