MOBILE WORLD CONGRESS 2025

Mavenir is pioneering 5G network monetization through its Converged Packet Core, which supports all network generations of technology, including Wi-Fi. The company’s monetization strategy includes adopting cloud-native principles, which allows for network disaggregation, flexible placement of workloads, open API operation model, reduced operational complexity with cloud-native automation. Mavenir’s Charging and Billing system is cloud-native by design and supports flexible charging models enabling Agile Monetization.

The support of Open API in all the interfaces creates a Network-as-a-Service platform fostering developer communities with accessible APIs and tools to accelerate innovation. Mavenir’s Converged Packet Core has AI/ML integrated natively to reduce TCO, optimize QoE, and monetize user data. The key focus areas of use cases for Mavenir have been Mobile Edge Computing, Network Slicing, Private Networks, Industrial IoT, Monetization and Service Optimization using AI/ML and Network Exposure. These strategies redefine 5G network possibilities, transforming industries, enhancing user experiences, and driving economic growth in a rapidly evolving digital landscape and hyperconnected world.

Telecom operators are increasingly turning to cloud-native automation to modernize their networks and keep pace with the demands of 5G and hyperconnectivity. Cloud-native automation, which leverages containerized infrastructure, microservices architecture, and open-source tools is seen as a key enabler for network modernization and monetization. Mavenir leverages insights and expertise gained from extensive global deployments to implement cloud-native automation, enhancing operational efficiency for operators. This strategy reduces complexity and yields significant cost savings compared to traditional methods, reflecting Mavenir’s commitment to innovation and excellence in telecommunications. This approach also allows for the efficient deployment, management, monitoring, and optimization of multi-cloud 5G networks, ultimately enabling the rapid innovation of new services.

This demo will showcase the automation of Mavenir’s Converged Packet Core Network Functions deployment using open-source tools and a GitOps-based automation framework.

In this demo, Mavenir presents its NIaaS, a holistic AI-native framework for telco networks, hosted in Mavenir’s RIC. The framework hosts a suite of advanced AI algorithms, in particular, Generative AI, Digital Twin, Deep Learning, etc. We present results of these advanced AI algorithms acting on commercial 4G/5G mobile traffic, live from the field deployment of a Tier-1 brownfield mobile network operator’s 5G NSA network. The results showcase remarkable insights and intelligence about the network towards optimization for tangible improvements in performance and user experience KPIs.

*Based on results of an AI-native Open RAN deployment using Mavenir RIC

*In collaboration with NVIDIA & AWS*

Demonstrating the potential of Generative AI with Large Language Models (LLMs) to build a Network Engineer CoPilot to automate ticket troubleshooting/ticket mining and enable incipient fault detection.

Operations teams and R&D engineers spend a significant amount of time debugging issues. Debugging is often a manual process that involves going through core dump stack traces and log traces to detect log anomalies, with very little assistance from automated or AI/ML based tools. This demo showcases the potential of GenAI to define a Service Assurance AI/Ops Platform that reduces operational and support effort and ensures that SLAs are maintained.

*In partnership with Microsoft*

The power of Open RAN lies in open interfaces, fostering an ecosystem for new use cases and increased network efficiency. Mavenir and Microsoft showcase the potential of Mavenir’s DU product using Microsoft’s Janus framework from the Programmable RAN platform. This demonstration unlocks value, enabling targeted debugging and facilitating the implementation of new functionalities like interference detection or energy savings by third parties.