One of many network-operations use cases. This example collapses the alarm storm across many management systems into the one service-impacting incident, with the institutional memory of every incident before it.
Proves these Lumina features
Episode 1: The Alarm Storm. A storm of a million events collapses to one incident, with auditable lineage. It runs where your data lives, up to fully air-gapped.
Your NOC drowns. Enterprise teams average more than 10,000 alerts a day, and fewer than 5% require human action. At peak, a national operator can see more than a million alarms a day across two dozen management systems. 85 to 95% is noise.
The root cause is rarely where the symptom appears. It hides across RAN, transport, core, and power, in different schemas. During one national outage, engineers had the diagnostic logs the whole time but could not assemble the answer for 14 hours. The data was there. The reasoning was not.
Traditional approaches were not built for the scale and complexity of modern operations.
Correlation engines suppress and group, but they do not reason about service impact across vendor silos. Engineers still stitch context from 25 systems by hand.
AIOps starts cold each time. The pattern a senior engineer recognized last quarter is re-learned from scratch, because nothing carried it forward.
Fault-tree tools work inside one domain. In a multi-vendor 5G network, the cause is in a domain other than the symptom, so single-domain RCA breaks.
When the answer requires assembling logs across systems under time pressure, and a risk algorithm downgrades a change because the first steps looked fine, the real signal stays buried.
Three layers of intelligence working together: reasoning agents, proactive detection, and multi-agent deliberation.
Agents reason across alarms, telemetry, topology, and tickets from every management system to one service-impacting incident with context. Every correlation runs as a verifiable query against the data you already stream, not a black box.
Every calculation is SQL you can verify. No black box.
Ingesting 41,280 alarms across 23 management systems (last 15 min)... Clustering by topology + timing correlation → 41,280 alarms resolve to 1 root incident Root: backhaul timing fault on aggregation ring AGG-114 Service impact: 38 eNodeBs, ~12,400 subscribers degraded → 3 downstream alarm groups are symptoms, suppressing
EARLY SIGNAL: Aggregation ring AGG-114 showing timing drift (+0.8ppm over 20 min) Pattern matches pre-cascade signature seen 3x in Cortex memory Confidence: HIGH → Recommend: transport team inspect AGG-114 before customer impact
The Radar continuously scans for the early signature that precedes a cascade: timing drift, error-rate creep, topology stress. It surfaces the incipient fault before the alarm flood begins.
The Radar surfaces issues the operator didn't know to look for. Before they become incidents.
RAN, transport, and core agents debate competing hypotheses into one governed root-cause verdict, with the human engineer holding veto. The recommendation is an action for your team to approve, never an unattended change to the network.
The output is grounded in facts (SQL results), not hallucination. Every recommendation carries a full audit trail.
RAN Agent: 38 cells down, recommend cell-level reset Transport Agent: all 38 sit behind AGG-114, this is transport, not RAN Core Agent: core healthy, no S1 anomalies Cortex: identical signature was a backhaul timing fault in March → Verdict: transport timing fault on AGG-114. Reset cells will not fix it. Route to transport on-call for approval.
Lumina addresses the four strategic problems that hold operators back.
One reasoning layer triages the storm across every vendor system, so engineers see incidents, not alarms. Documented AIOps deployments cut alert volume 80 to 95% and MTTR 50 to 75%.
Catch the incipient fault before the cascade, and resolve the real one faster. Every hour of a major incident is rig-grade expensive in a telecom network.
With Cortex, every triaged incident teaches the system. The 3am signature a senior engineer recognized is institutional memory, not tribal knowledge that retires.
Every correlation and root-cause claim is backed by a query you can inspect. Recommendations route to your team for approval. Lumina never touches the network of record unattended.
Specialized AI agents that power this workflow.
Incident Correlator
Collapses multi-system alarm storms into service-impacting incidents using topology and timing correlation.
Transport & Core Analyst
Reasons across RAN, transport, and core domains to locate the cause where the symptom is not.
Sovereignty & Custody
Keeps every query inside your environment, so the whole triage runs where your network data lives.
This is just one of many use cases
NOC alarm triage & event correlation is one example of how Lumina reasons on operational data. Across Telecom, every domain has use cases where AI agents can add value.
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View all Telecom use cases