RAGFlow
A retrieval-augmented generation framework with agent capabilities for building production AI systems
- Also known as
- ragflow
What is RAGFlow?
An AI platform that combines retrieval-augmented generation with autonomous agent features, enabling developers to create production-ready AI systems from complex data sources. It supports multiple deployment models (cloud or self-hosted Docker), integrates with various LLM providers and data sources, and provides streamlined workflows for enterprises of any scale.
Platform & deployment
Independently observed- CLI
- Web
- Cloud / SaaS
- Self-hosted
Integrations (12)
Independently observed- Discord
- Feishu
- Telegram
- Line
- Confluence
- S3
- Notion
- Google Drive
- OpenAI
- DeepSeek
- Gemini
- OpenClaw
RAGFlow alternatives
Other rag tools we track, ranked by the same independent score.
- RagieA managed service that automates document ingestion, parsing, and intelligent retrieval for AI applicationsmedium · 55%
- LightRAGlow · 16%
- Amazon Bedrock Knowledge BasesManaged retrieval-augmented generation service that connects AI applications to proprietary enterprise datamedium · 62%
- PathwayA streaming data framework for building real-time AI and ML applicationslow · 36%
- Ragaslow · 27%
- Contextual AIlow · 41%
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for RAGFlow, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Pricing transparency | 25 | 0.08 | 2.1 | ✓ |
| Integrations | 32 | 0.04 | 1.3 | ✓ |
| Price level | 0 | 0.05 | 0.0 | - |
| Reliability | 0 | 0.07 | 0.0 | - |
| Capabilities | 0 | 0.05 | 0.0 | - |
| Security posture | 0 | 0.07 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.