Guavus announced a new product, called Guavus Alarm IQ, which uses advanced AI and machine learning algorithms to help CSPs to identify efficient ways to manage network alarms with a view to resolving the most critical network issues.
Alarm IQ automatically analyzes streams of alarms, classifies them, and predicts which alarms will lead to incidents. Guavus claims that the new prodyct can reduce the number of alarms network operators need to pay attention to by more than 90%. This dramatic shift enables network operations center (NOC) teams to prioritize their resources and deliver a much higher level of service to their internal and external customers at a reduced cost.
Alarm IQ is built on the Guavus Reflex AI-powered analytics platform, which supports a wide range of applications as well as customizable ‘self-service analytics.’ CSPs can take advantage of Alarm IQ for alarm management and easily expand to leverage Reflex AI-based analytics for advanced network planning and operations, mobile traffic analytics, marketing, customer care, security and IoT – or to build their own custom applications.
Stephen Spellicy, VP of Products and Marketing, Guavus
The problem is distinguishing the noise from the signal. Standard alarm de-duplication and management tools classify 10-20% of the alarms as critical, which is still too many to handle in one day. In actual field trials of Alarm IQ, network operators were able to reduce the number of alarms by more than 90%.
Adaora Okeleke, Senior Analyst, Ovum Research
Alarm IQ uses AI-based analytics to get a better understanding of which network alarms are service-impacting, enabling CSPs to transform the way network issues are addressed and improve customer experience.
