Modern AI infrastructure increasingly depends on autonomous runtime systems operating continuously across distributed environments. AI systems now: orchestrate cloud-native infrastructure automate operational workflows coordinate distributed runtime execution execute regulated compute actions operate continuously at machine speed Traditional security systems primarily: monitor runtime activity analyze telemetry after execution inspect logs retrospectively respond after operat

Modern AI infrastructure increasingly operates through autonomous runtime systems executing continuously across distributed environments. AI systems now: automate operational workflows coordinate runtime orchestration manage cloud-native infrastructure execute regulated compute processes operate continuously at machine speed Traditional security systems primarily: monitor runtime activity analyze telemetry after execution inspect logs retrospectively respond after operational

Modern AI infrastructure increasingly operates through autonomous runtime systems executing continuously across distributed environments. AI systems now: automate infrastructure orchestration coordinate runtime operations execute regulated compute workflows manage cloud-native infrastructure trigger machine-speed operational decisions Traditional security architectures primarily: monitor runtime activity inspect logs after execution analyze telemetry retrospectively respond a

Runtime authorization artifacts establish cryptographic execution trust before runtime execution begins, enabling fail-closed governed execution infrastructure. Modern infrastructure authenticates: users services devices networks applications But most systems still do not authenticate execution itself. This is the next infrastructure gap. As autonomous systems increasingly control: AI inference financial operations distributed agents infrastructure orchestration regulated aut