The Developer’s Guide to RAG with Data Streaming
RAG enhances LLM accuracy by incorporating real-time data, but scaling it reliably requires an event-driven architecture. This guide explores how to build real-time GenAI applications using a data streaming platform, detailing core RAG patterns, data augmentation, inference, and orchestration. It also highlights tools like Flink, connectors, and Stream Governance, supported by practical use cases and reference architectures.
RAG enhances LLM accuracy by incorporating real-time data, but scaling it reliably requires an event-driven architecture. This guide explores how to build real-time GenAI applications using a data streaming platform, detailing core RAG patterns, data augmentation, inference, and orchestration. It also highlights tools like Flink, connectors, and Stream Governance, supported by practical use cases and reference architectures.