Does it fix the problem, and prove the fix held before it closes the ticket?

Rolls back, scales, restarts or opens a PR, then re-checks the signals that fired and holds a stability window before closing the incident and learning from it.

Can you dial exactly how much it does on its own, pattern by pattern?

Autonomous, human-in-the-loop or advisory, set per pattern, with blast-radius caps, approval policy, a mid-incident kill switch and a full audit trail.

Can it find a root cause in a different domain than the symptom, in minutes?

Specialist agents test hypotheses in parallel across network, compute, storage, database, security and cloud, score each with a confidence level, and return one explainable root cause.

Can it map every entity, from pod to PDU, and what each one touches, in real time?

One live, normalized model of hosts, services, GPU nodes, switches, cabinets, PDUs, databases and IAM roles, with relationships and lineage on every fact.

Is it useful on day one, and does it get sharper after every incident on its own?

500+ curated skills from decades of operations, your runbooks with private, team or org scope, and every resolved incident folded back in.

Can it cut thousands of events to the few that matter, before they reach a human or a model?

Deduplicates, groups and correlates raw events into a handful of real incidents. In a representative deployment, 4,287 events became 12 incidents an hour.

Does it see cloud, datacenter, facilities, tickets and chat, without a migration project?

50+ integrations across observability, cloud, UnityOne DCIM, datacenter collectors, ITSM, email and chat, through deep integration or light discovery. No migration project.