Drivers for AI Enhancement
Real-time service quality assurance for rapidly evolving customer requirements
End to end, customer-centric automation for enabling zero-touch operations
Operational scalability to address the growing demand for a variety of mobile services
CapEx efficiency through improved utilization of existing resources & precise network planning
AI Solutions
Predictive Energy Saving
Predictive Energy Saving analyzes historical network data, extracts patterns and proactively shuts down the under utilized carriers with traffic lower than a predicted threshold in a given time frame.
Predictive Network Load Balancing
The solution forecasts capacity utilization levels of the network at a cluster level and proactively moves the traffic from carriers that might face a potential increase in utilization to neighbor carriers to preserve customer experience.
Smart Network Planning
The solution predicts long term capacity demand by correlating multiple data sources. Based on the forecast, it generates the optimum investment plan in line with operator’s financial & technology policies.
Anomaly Based Unplanned Event Handling
The solution tracks traffic anomalies at a cell level on a 7x24 basis and identifies potential traffic surges based on historical traffic trends. Once an anomaly is predicted, it takes proactive capacity and coverage actions.
Geo-Based Experience Management
The solution takes location-based optimization actions for specific customer groups. It uses machine learning to classify sites for different customers routes (i.e., highways, parks etc.) to take targeted actions.
Dynamic Slice Optimization
The solution identifies services with different SLA requirements. Then it adjusts the network parameters based on these SLA requirements and historical network data to allocate virtual network resources to each service.