RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine designed to enhance AI agents by providing truthful question-answering capabilities supported by citations from complex formatted data. It integrates with large language models (LLMs) and uses a converged context engine alongside pre-built agent templates to convert complex data into production-ready outputs.