About this video
Most organizations are running AI in their security workflows. Few have it governed. This walkthrough shows what governance looks like in practice — not as a compliance checkbox, but as a design constraint that makes AI-generated threat outputs defensible, repeatable, and traceable back to real architecture.
The session covers all four Nexus MCP use cases with live product demonstration: IDE threat modeling, document-based model generation, CI/CD pipeline integration, and portfolio-level analysis. Each demo uses the same underlying system — ThreatModeler as the governed system of record, AI agents as the workflow layer.
What you'll learn
- Why architecture context is the prerequisite for AI outputs worth acting on
- ✓How the MCP protocol connects AI agents to ThreatModeler's rules engine and threat libraries
- What continuous threat modeling looks like embedded in a real CI/CD pipeline
- How security and engineering leaders can report on portfolio-wide risk from a single governed source
Presenters
Ben Oster
Chief Product Officer
Anthony Lombardo
Vice President, Marketing
Mike LeBlanc
Chief Revenue Officer
![[DEMO] Data Analysis Techniques](https://cdn.prod.website-files.com/6a33a0a14a58dc64ba25bb77/6a43e13bf8c9c327c331409d_image17.jpeg)
![[DEMO] Data Security Best Practices](https://cdn.prod.website-files.com/6a33a0a14a58dc64ba25bb77/6a43e13bf8c9c327c3314097_image15.jpeg)
![[DEMO] Data Cleaning Techniques](https://cdn.prod.website-files.com/6a33a0a14a58dc64ba25bb77/6a43e13bf8c9c327c3314094_image13.jpeg)