Microsoft Copilot Architecture | What's behind Copilot? | LLMs, Microsoft Graph, Vector Search

Welcome to a comprehensive video on the architecture of Microsoft Copilot!

In this video, we explore the intricate workings behind the scenes, going beyond just the architecture to delve into critical components such as grounding processes, semantic index, and the role of Microsoft Graph.

🔍 Topics Covered:

Service Boundary: Ensuring your data never leaves your organization.

User Prompts: How requests are handled and processed.

Grounding Process: Adding context to user requests.

Third-Party Integration: Connecting with applications like Salesforce and ServiceNow.

Microsoft Graph: Centralizing data and enabling connectivity.

Large Language Models (LLMs): Interpreting and responding to user prompts.

Compliance and Security: Ensuring data access policies are adhered to.

Quality Factors: Importance of prompt quality, data integrity, and ethical AI.

Join me as I break down the six-step process of Copilot, providing clarity on how it functions similarly to systems like ChatGPT and Perplexity.

This session is essential for anyone looking to understand the robust capabilities and secure environment that Microsoft 365 Copilot offers.

Feel free to ask questions in the comments, and stay updated as we continue to explore the evolving landscape of AI and its applications.

-Yatharth Kapoor