In this session, we’ll go end-to-end and build a real RAG system on Azure Kubernetes Service (AKS) using the KAITO RAG Engine.

You’ll see how to:
- Install and run KAITO RAG Engine on AKS
- Understand the RAG architecture (ingestion, embedding, retrieval, inference)
- Ingest and index real documents into the RAG Engine
- Connect the system to a Streamlit-based chatbot UI
- Query your own data using an LLM—live and in real time

The session is practical, code-driven, and demo-heavy, with a focus on how these components fit together in a cloud-native, scalable architecture.

Whether you’re a cloud engineer, platform engineer, or AI developer, you’ll walk away with a clear mental model—and a working reference—of how to deploy RAG systems on Kubernetes.

Prefer time slot in between 10am to 2pm. Otherwise, flexibile.