Modernizing the SOC for Scale

Why Security Consolidation Fails and How AI/ML-Driven SOCs Fix It

Despite major investments in consolidation, SOCs still struggle with alert fatigue, slow detection, and fragmented visibility. This whitepaper reveals why traditional SIEM models fail to scale, and how AI/ML-driven, pre-alert intelligence reduces false positives, enables sub-5-minute detection and response, and automates security at scale while lowering costs.

FI-Tool consolidation

A Quick Glimpse Inside the Whitepaper:

This whitepaper reveals why security tool consolidation continues to fall short in modern SOCs, and how traditional SIEM-led architectures struggle to scale across identity, endpoint, network, and cloud environments.

Here’s what makes it worth your time:

  • Why loosely integrated platforms still generate high false positives, delayed detection, and heavy manual correlation.

  • How post-ingest detection models create scaling limits, correlation gaps, and operational bottlenecks in high-EPS environments.

  • Why AI/ML-driven, Dynamic Threat Model (DTM) architectures enable pre-alert correlation, sub-5-minute detection, automated response, and measurable cost reduction.

This whitepaper focuses on modernizing SOC operations to reduce alert fatigue, improve analyst productivity, and deliver intelligence-driven security at scale.

Ready to see how AI-native security changes the outcome?