Session Abstract

Copilot Studio becomes far more useful when it can retrieve the right information at the right time. For many organizations, that means moving beyond simple knowledge sources and connecting agents to structured, searchable data using Azure AI Search. In this session, we focus on both the why and the how of integrating Azure AI Search with Copilot Studio. We start by examining the types of problems this approach actually solves, including large content sets, fragmented knowledge, and the need for predictable retrieval. From there, we walk through how the integration works, what decisions matter during setup, and how design choices affect agent behavior and response quality. Rather than following a single recipe, the session highlights key considerations such as indexing strategy, data shaping, query behavior, and how Copilot Studio consumes search results. You will see how different choices influence accuracy, performance, and maintainability as solutions grow.

Michael Heath

Michael Heath is an innovation strategist and Frontier Firm advisor who helps organizations move from digital transformation to intelligent transformation. With over 15 years of experience across the Microsoft ecosystem and enterprise technology, he partners with leaders to align people, platforms, and purpose through AI, automation, and data. Michael focuses on translating strategy into practical execution, helping organizations scale intelligent systems in ways teams adopt and sustain.