Airport cyber incident investigations often involve records scattered across enterprise networks, airport operations systems, access-control platforms, badge records, baggage systems, flight-information displays, gate systems, vendor maintenance access, camera metadata, facility-control systems, security tools, and operational event records. REMI AI brings those mixed sources together and generates a cyber SITREP that explains the situation in plain English. It identifies what happened, how access was achieved, which systems were touched, whether airport operations or facility-control activity occurred, where suspicious files or AI-spawned tools appeared, what remains unproven, and which records support the sequence.

REMI is trained to identify adversarial behaviors associated with advanced AI attacks, AI-controlled malware, and hybrid attack patterns across airport and tower system logs. It analyzes suspicious access, out-of-pattern system changes, unexpected communications, and coordinated events to surface behaviors that may indicate staged or AI-assisted attacker activity.

REMI turns correlated evidence into the supported explanation of how the activity unfolded and why the warning signs did not become obvious sooner.

Analysis uses the connected evidence path to explain how access was achieved, how activity moved, which systems or airport areas were affected, why alerts or controls did not tell the full story, what evidence supports each conclusion, and what remains unresolved.