Most AI implementations focus on retrieval—finding information that exists. But in high-stakes industries like compliance, legal, and ESG, the most critical question isn't "What is there?" but rather "What is missing?"

Traditional RAG (Retrieval-Augmented Generation) patterns often fail at gap analysis because they rely on semantic similarity, which struggles to identify incomplete information. To solve this, we need to move from simple pipelines to Agentic Reasoning.

In this session, I will demonstrate an Agentic Auditor that performs automated gap analysis of an answer against a structured checklist. We will dive deep into how an agent can "reason" through a checklist to identify semantic discrepancies and missing requirements.