Most RAG failures start before retrieval: the document was parsed poorly, chunked blindly, or stripped of structure. RAGFlow treats the context layer as something to engineer, not just embed.
What Sets It Apart
It emphasizes deep parsing for PDFs, Office files, scans, images, structured data, and web content. Template chunking, visible citations, hybrid search, reranking, APIs, and agent templates create a path from raw documents to production workflows.
Who Should Use It
Great fit if your RAG problem is dominated by complex documents, traceability, and workflow. Look elsewhere if you only need a small embedding demo or minimal vector search API.
