From Data to Decisions: The Architecture of Context Engineering

Hack Session

About the session

Enterprise AI does not usually fail because the model is incapable, it fails because the model receives the wrong context, incomplete context, or too much context at the wrong time.

This session explores how context engineering can be used to build AI systems that understand not just a user’s question, but also the business meaning, data relationships, analytical sequence, and decision intent behind it. Using a real enterprise analytics use case involving hundreds of cross tabs and complex research data, the session will demonstrate how structured metadata, sequential context, semantic retrieval, intelligent ranking, and validation work together to surface the right evidence for every query.

The focus will be on the actual architecture and design choices behind the solution: how context is generated, enriched, retrieved, prioritized, and continuously improved. Attendees will leave with a practical understanding of why context engineering is becoming the foundation for reliable, scalable, and production-ready enterprise AI.

Speaker

Download Brochure