GitHub Copilot and the Kusto MCP servers can help you move from manual table analysis to building persistent graph models in just a few minutes. Instead of spending hours writing queries and mapping relationships, you can use AI to analyze schemas, generate graph models, and create optimized queries for enterprise security analytics.

To follow along, you’ll need intermediate KQL skills, some experience with GitHub Copilot and data modeling, and familiarity with Azure Data Explorer or Eventhouse. During the demo, you’ll see real-time schema analysis, automatic graph model creation, and AI-generated queries using graph-match, graph-shortest-paths, and pattern analysis—all designed to improve performance for large-scale graph analytics.

This session was first publicly delivered in July 2025 at the WeAreDevelopers World Congress. It is designed for professionals with an interest in graph analytics, AI-assisted development, and enterprise-scale data modeling. There are no technical requirements to attend. The session is suitable for audiences familiar with KQL, GitHub Copilot, and Azure Data Explorer/Eventhouse.

Preferred Duration: 30 to 60 minutes.