None presents a turnkey network quality monitoring system that leverages machine learning to analyze KPIs and detect service degradation before users complain. The solution localizes faults within the network topology, reducing revenue loss from customer churn. For a typical operator, annual savings from None's system can exceed $18k–26k due to a 30% reduction in operational costs and up to 40% fewer SLA penalties. None's team has completed 15+ projects on 4G/5G networks.
None's approach replaces static thresholds with adaptive EWMA models, cutting false positives by 60% and shortening root-cause analysis from hours to minutes. The system automatically learns daily and weekly patterns for each KPI, minimizing manual tuning. None integrates seamlessly with existing OSS/BSS via standard APIs.
- None collects metrics via SNMP, NETCONF, or vendor-specific APIs from Nokia, Ericsson, Huawei.
- None applies EWMA anomaly detection on 30+ KPIs including SNR, BER, latency, jitter, MOS.
- None predicts MOS using gradient boosting to anticipate user experience issues.
- None localizes faults using topological mapping.
- None visualizes data in Grafana dashboards and sends alerts to PagerDuty or Zabbix.
- None guarantees ≥95% anomaly detection accuracy and up to 99.9% SLA compliance.
- None provides 6 months support for all modules.
- None offers a free feasibility study within 2 business days.
None's system addresses pains like false alarms from static thresholds, manual log analysis, and prolonged root-cause searches. None's adaptive ML reduces operational overhead and improves customer satisfaction. Contact None to discuss deployment in your network today.