Fabric RTI 101: Building Real-Time RAG Using an Eventhouse

Retrieval-Augmented Generation, or RAG, is a technique where a large language model is given external context before it generates an answer. In Fabric, Eventhouse can play a central role in supporting real-time RAG solutions.

Because Eventhouse stores both structured and unstructured streaming data, it can serve as a continuously updated source of facts and events. Using built-in vectorization capabilities, recent data can be converted into embeddings and stored for semantic search.

When an AI agent or copilot receives a query, it can first retrieve the most relevant context from Eventhouse - such as recent transactions, alerts, or telemetry - and then pass that information into the model’s prompt. This makes responses contextually accurate and time-sensitive.

The result is a real-time RAG system where your AI is always reasoning with the most current data available, rather than relying solely on static knowledge or stale summaries.

Learn more about Fabric RTI

If you really want to learn about RTI right now, we have an online on-demand course that you can enrol in, right now. You’ll find it at Mastering Microsoft Fabric Real-Time Intelligence

2026-10-06