CrewAI AMP vs OpenRAG
CrewAI AMP
crewai.comOpenRAG
open-rag.aiSide by side
| Figure | CrewAI AMP | OpenRAG |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 2 |
| Spec score · LLM Application Development Frameworks | 8.0 (#8) | 8.3 (#5) |
| Integrations | The pricing page lists GitHub integration, while the documentation describes triggers for Gmail, Slack, Salesforce, and other services. | The product documents compatibility with OpenAI API clients and names Open WebUI, LangChain, n8n and Twake.ai as integrations. |
| Purpose | CrewAI AMP is an agent management platform for building, deploying, governing, and scaling AI agent workflows across enterprise applications, with or without code. | OpenRAG is a modular framework for building document-grounded retrieval-augmented generation systems. |
| Support | The pricing comparison lists community support for both plans and dedicated, Slack/Teams, and on-site support for Enterprise. | The product site directs technical questions to GitHub issues and links to documentation and a contact form. |
Plans
OpenRAG
- OpenRAG (AGPL-3.0 self-hosted)Free
- Managed OpenRAG servicePriced on request
In their own words
OpenRAG
OpenRAG is a modular framework for building systems that answer questions using documents as their grounding. Its retrieval combines semantic search with BM25 keyword matching and multilingual reranking; answers cite a source document and page, with links to the cited location. Document processing covers listed text, office, email, audio, video, and image formats, with PDF layout awareness, OCR, image captioning, and audio transcription. The product includes an admin console, chat interface, and OpenAI-compatible API, and can connect to user-provided models or a hosted provider. Partition isolation, owner, editor, and viewer roles, plus token or OpenID Connect authentication, are among its access controls. It can run on infrastructure controlled by the deployer, keeping documents, embeddings, and queries within that environment. The self-hosted AGPL-3.0 edition is listed at free. Deployment prerequisites are Docker, Docker Compose, and at least 16 GB of RAM; a CPU-only profile is optional. CSV, ODT, and HTML support, tool calling, agentic RAG, MCP, and encryption in transit and at rest are listed as coming soon.