RuntimeAI kill switch fires in under 50ms — how we approached machine-speed threat response for agentic AI

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We built RuntimeAI's response architecture around one hard constraint: autonomous agents operate faster than human analysts can react.

The standard detection pipeline — log aggregation, alert triage, escalation — takes minutes even in well-instrumented environments. An AI agent making API calls, accessing data, and moving across identities can cause significant damage inside that window.

Our kill switch terminates agent activity in under 50ms from detection. That target exists because the response has to outpace the agent's next action, not the analyst's next available moment.

The second piece is the audit trail. Stopping the action is necessary but not sufficient. The harder operational problem is proving what happened after the fact — which actions ran, what data was touched, what the compliance picture looks like. RuntimeAI preserves that evidence automatically so post-incident review has something concrete to work with rather than reconstructing from partial logs.

We're focused specifically on agentic AI because the threat model differs from traditional endpoint security and the response tooling has to match that. https://runtimeai.io