From Zero to AI: Build Your Flexible AI Assistant With Quarkus in Just One Day!

This computer-free, architecture-focused workshop guides participants through the structured design of an enterprise-grade AI assistant capable of indexing and interpreting internal knowledge sources such as Confluence and SharePoint. Through collaborative modeling exercises, architecture canvases, and process simulations, participants explore how retrieval-augmented generation (RAG), secure data ingestion, and Quarkus-based service orchestration work together to form a robust solution.

The session covers the key architectural components required to integrate LLMs with internal content repositories, including indexing pipelines, chunking strategies, metadata handling, access control, and query routing. Using tangible building blocks and guided role-based simulations, participants will design the complete end-to-end system — from ingestion flows and vector retrieval layers to the AI interaction model and Quarkus service topology.

Suited for developers, architects, and technical leads, this workshop delivers a clear and practical understanding of how to architect a scalable, maintainable AI assistant for enterprise knowledge platforms, leveraging proven patterns from Quarkus and modern AI systems — all without writing any code.