Traditional artificial intelligence models rely on outdated training data and public sources, creating vulnerabilities in cybersecurity applications. Retrieval Augmented Generation, or RAG, offers organizations a pathway to constrain AI responses to trusted, proprietary data sources while maintaining real-time relevance and auditability.

This emerging framework transforms how security teams approach threat detection, compliance analysis and incident response by combining institutional knowledge with advanced AI capabilities.

In this insightful session, Taka Ariga, former chief AI and data officer at the U.S. Office of Personnel Management, and Brennan Lodge, founder of BLodgic, discuss:

• How RAG architectures enhance SOC team efficiency through contextual threat intelligence;
• Strategic implementation approaches for GRC teams managing regulatory compliance gaps;
• Practical frameworks for scaling AI solutions from prototype to production environments.