Consolidation gives
CERNE breadth. Its agentic intelligence gives it depth. CERNE is structured as a layered system that moves from raw signal to reasoned action:
A data and context layer unifies telemetry, events, topology, CMDB, business context, and historical baselines — so the platform understands not just what is happening, but why it matters.
An intelligence and agentic AI layer analyzes those signals, detects patterns, predicts outcomes, and performs root-cause analysis and blast-radius prediction. It generates next-best-action recommendations and predictive alerts across performance, cost, and security — with confidence scoring so you know how much to trust each conclusion.
An automation layer closes the loop, connecting workflows, remediation, approvals, and ITSM processes so insight turns into action.
A security and governance layer protects all of it with identity management, tenant isolation, encryption, auditability, and policy enforcement.
An interaction layer — where the LUMI copilot lives — surfaces everything through dashboards, alerts, reports, and natural-language conversation, tailored to every persona on the team.
Crucially, this isn’t a single model answering questions. CERNE can orchestrate multiple specialized AI agents that collaboratively investigate an issue and drive it to resolution, governed by policy and human-in-the-loop approval. It’s the difference between a tool that tells you there’s a problem and a system that helps you fix it.
