Smart Diagnostics with AI-Powered Networking for Enhanced QoE
CSP service desk representatives are empowered with intuitive, insightful on-the-spot diagnostic tools to troubleshoot L2 connectivity issues. RADinsight SD improves first call resolution, helping service desk representatives to easily isolate the issue and provide the customer with insightful diagnostics. It goes beyond traditional performance monitoring with intuitive end-to-end visibility across the customer LAN, CSP network (WAN) and internet/cloud.
Key Take-Aways
Continuous Monitoring
End-to-end connectivity KPIs and ML-based analytics
Automated Resolution
Problem observation and remedy recommendations in plain language
How The Lack of End-to-End Service Visibility Hurts Your Customers and Your Business
According to a global survey conducted among CSPs, (L2 business services and 5G xHaul), the source of 76% of business connectivity problems reported to CSP service desks lie outside the CSP’s scope of control.
Yet, your service desk and operations personnel spend valuable time and resources trying to locate, isolate and identify the issues, leaving your customers frustrated and their business disturbed.
Improve Quality of Experience and First Call Resolution
RADinsight SD helps you avoid these challenges by:
Helping service desk representatives easily isolate the issue.
Providing the customer with insightful diagnostics.
Offering intuitive end-to-end visibility across customer LAN, CSP network (WAN), and Internet/cloud applications.
Highlights
Continuous end-to-end connectivity KPIs monitoring, and ML-based analytics
Plain language recommendations that direct customers to specific areas for remedy or improvement.
Virtual ticketing mechanism for documentation, history, and operational collaboration.
Self-diagnostics portal helps customers identify and often resolve the problems from their end, avoiding calls to CSP Customer Care.
Dashboards display an at-a-glance, end-to-end view of connectivity path health for CSP call center personnel
Users view diagnostics for network degradation and root cause connectivity segments based on demarcation point analytics from the edge
QoS scores provided based on the history of a connectivity problem over time (evolution, persistence) as well as severity on top of network KPI analytics
AI/ML-driven analytics provide insightful feedback for next best action
Leverage EAD/NID/NTE installed base – does not require software agents or probes
RADinsight Smart Diagnostics
AI driven service assurance from the customer edge to the cloud
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