Artificial Intelligence and Machine Learning Solutions for Mobile Networks
We work with Mobile Network Operators to optimize RAN & Telco Cloud investments using Artificial Intelligence and Machine Learning technology. As Telco Clouds move towards disaggregated, distributed and open architectures, it creates tremendous opportunities for Machine Learning Technology to use real time telemetry data, historic demand data and external data sources to predict demand for various network components, predict KPIs for upcoming change in demand and to predict failures in the network.
Our team brings in decades of experience in the Telecommunications industry and deploying Machine Learning solutions in production networks that bring measurable business outcomes.
Solutions for Radio Access Networks and Telco Clouds
Dynamic Demand Prediction & Response
Aggregate customer demand changes dynamically based on seasonality, subscriber consumption patterns, Over-the-Top service offerings and other external factors. Predict demand for your RAN, Packet Core, Applications and other network resources. Dynamically reconfigure Edge Computing resources, RAN configurations and VNFs to provide optimal demand response to changes in demand to maximize profit.
Radio capacity optimization
Turbo-charge cell site installation and tuning processes with automated configurations using machine learning models. Correlate cell-trace data, RF site parameters and KPIs to tune your network continuously to deliver superior subscriber experience with your existing radio capacity investments.
KPI and Fault Prediction
Telco Clouds provide hidden indicators that are discovered by Machine Learning algorithms to identify causal relationships, patterns and issues leading up to a failure event or drop in KPIs. With advanced notifications, remediation advisories and closed-loop automation, our solutions can help manage subscriber churn, minimize SLA penalties and optimize operations expenses.
Mobile Networks continue to see significant growth in video traffic that drive capacity upgrades across various layers of the network. Optimize network resources and improve customer experience by predicting content consumption and moving content closer to the mobile edge.
Intelligent network Slicing
Next Generation Mobile Networks seek optimization strategies to meet customer SLAs and rapidly deploy new network services. Develop Network Slicing configurations based on inputs from thousands of variables for various market segments, services and business metrics with our Machine Learning solutions.
Mobile Networks have tremendous real-time intelligence to assist autonomous vehicle software and participate in future V2X networks. Create new revenue streams by monetizing your network intelligence, edge computing capacity and improving your position in the Autonomous Driving value chain.