Most incident-response tooling is fragmented: one tool detects, another diagnoses, and a human resolves. The handoffs between these stages are where time is lost. Kersev AI unifies them into a single closed loop.
1. Detect — kernel-deep telemetry
We collect continuous telemetry from the kernel, hypervisor, and network paths. This isn't log scraping — it's real-time instrumentation of the systems that actually fail. Anomalies are surfaced the moment they form.
2. Diagnose — causal reasoning
Detection without diagnosis is just noise. Our causal reasoning engine correlates signals across the stack to identify root cause, not just symptoms. It answers the question every on-call engineer asks at 3 a.m.: why is this happening?
3. Resolve — policy-bounded autonomy
Once root cause is identified, Kersev AI can execute remediations — within policy boundaries you define. Restart a degraded service. Rebalance a saturated node. Drain a failing host. Every action is logged, reversible where possible, and auditable after the fact.
The closed loop
Because detection, diagnosis, and resolution are unified, the loop tightens. Resolution feeds back into detection: the system learns which patterns lead to which failures. Over time, the loop gets faster, quieter, and more accurate. That's the difference between an alerting tool and an autonomous platform.