Agama Technologies has introduced a new AI-based extension to its solution that improves the precision at which alarms are triggered.
The new AI Anomaly Detection automatically identifies anomalies based on information from every subscriber on an operator’s network and provides actionable alerts, clear visualization of detected anomalies and powerful interactive analytics.
“We are excited to introduce the new AI Anomaly Detection feature,” says Johan Görsjö, director of product management, Agama Technologies. “Separating actual anomalies from normal variations in KPIs is an excellent example of how AI and machine learning can be applied to video service assurance in a way that addresses real-world needs.”
Agama’s AI Anomaly Detection uses automated self-learning to recognise patterns in video delivery networks. Acting on information collected in real-time from as many as several million client devices, such as set-top boxes and OTT player applications, the algorithm predicts how each subset of the population, from whole countries down to individual neighbourhoods, will behave based on past observations.