As enterprises and public sector organizations move beyond generative AI toward autonomous, agentic systems, the ability to understand relationships, context, and operational dependencies has become increasingly critical. Join us with guest speaker Karthi Subramaniam, Founder of Frizb, for a live webinar exploring how graph technologies provide the foundation for operational intelligence and next-generation AI systems.
Learn how graphs enable AI agents to reason across connected data, improve decision transparency, and accelerate root cause analysis in complex operational environments. Attendees will also discover how graph-powered systems support government and critical infrastructure use cases, including mission planning, security monitoring, asset tracking, and investigation workflows where accountability and traceability are essential.
Karthi Subramaniam discusses how graph technologies provide the foundation for operational intelligence and next-gen AI systems.
About the host
Karthi Subramaniam is the founder of Frizb, a supervisory intelligence platform for critical physical infrastructure. With over 20 years in software, networking, and cloud systems, he has focused Frizb on a specific unsolved problem: physical operations generate enormous volumes of multimodal signals across cameras, sensors, telemetry, and OT systems, yet no system connects them into operational understanding. Frizb's four-layer pipeline (Observe, Correlate, Reason, Report) addresses this with a graph-based correlation engine that maps causal relationships across heterogeneous event streams in real time.
Karthi's current focus is the intersection of graph-based event correlation and foundation models for grid infrastructure. Working with researchers across national labs and universities, Frizb is building and hardening Grid-specific models that reason over knowledge graphs of physical operational state. The core insight: physical incidents are cascading sequences of causally linked signals. Graph-based reasoning, anchored on an event and traversing candidate relationships, makes automated root cause analysis possible at the speed operational safety demands.