Building High-Fidelity Threat Intel Feeds for Agentic AI

Security teams rely on high-quality threat intelligence, yet consolidating data from dozens of sources remains a major challenge. This session breaks down how to build a custom intelligence feed that reduces noise, improves data quality, and supports AI-driven security operations.

You’ll learn how to collect, normalize, and enrich threat data so it’s consistent, contextualized, and ready for advanced analysis. We also look at how curated, high-fidelity intelligence strengthens AI models—enhancing pattern detection, improving classification, and enabling more proactive defense decisions.

What is covered:

• When it makes sense to build your own intelligence feed
  The core data sources that matter—and how to aggregate them effectively
  Practical methods for normalizing, enriching, and prioritizing threat indicators
• How high-quality, tailored datasets improve AI accuracy, precision, and reduce bias
• How AI systems leverage custom feeds to produce meaningful security insights
• Key resources to accelerate development, including the ReversingLabs Flexible Threat Intelligence Feed

Watch now!