Beyond the LLM: AI That Understands Before It Speaks.

About this session

Most AI applications follow the same pattern: collect data, send it to an LLM, and generate an answer. I believe that approach breaks down when decisions have real-world consequences, especially in healthcare. In this talk, I’ll share how building DrunR led us to a different architecture, one that transforms multimodal data into an explainable understanding of a person’s state before an LLM ever generates a recommendation. You’ll leave with a practical framework for building AI systems that are more trustworthy, more personalized, and designed to support better decisions, not just better conversations.