Telecom Predictive Condition Intelligence
This AI solution applies advanced analytics, federated learning, and predictive modeling to continuously monitor telecom infrastructure, radio links, and enterprise networks for early signs of failure or congestion. By anticipating equipment issues and network degradations before they impact service, it enables proactive maintenance, optimizes NOC operations, and reduces unplanned downtime, truck rolls, and SLA penalties.
The Problem
“Predict failures and congestion across telecom networks before customers notice”
Organizations face these key challenges:
Alert storms and noisy alarms hide the few issues that actually become outages
Unplanned downtime drives SLA penalties, churn risk, and emergency truck rolls
Telemetry is siloed across RAN/transport/core/enterprise domains and vendor stacks
Reactive troubleshooting wastes NOC time and yields inconsistent root-cause calls