TX-MAVENIR
11.6.2024 15:01:33 CEST | Business Wire | Press release
Mavenir, the cloud-native network infrastructure provider building the future of networks, today announced that it has pioneered a breakthrough Operations Co-Pilot that harnesses the power of generative AI (GenAI) to improve service-level agreements (SLAs) and optimize operational efficiency for communications service providers (CSPs). The innovation, which has been developed in collaboration with NVIDIA and Amazon Web Services (AWS), showcases the potential of GenAI to effectively define a Service Assurance AI/Ops Platform – reducing the burden on operations, support and maintenance teams and enhancing their ability to meet SLAs.
Mavenir’s Operations Co-Pilot for RAN Service Assurance (RSA) automates network troubleshooting, enabling mobile network operators to rapidly and accurately anticipate network issues and address detected network impairments before they become critical. The Operations Co-Pilot significantly reduces manual debugging effort, development and maintenance lead times to enhance IT operations, service availability and delivery for increasingly complex mobile networks.
Utilizing the power of GenAI with large language models (LLMs) trained on detailed key performance indicators (KPIs), counters, logs and traces from network infrastructure, Mavenir, together with NVIDIA and AWS, is creating a suite of Operations Co-Pilot solutions that will transform the operations management of telecom networks through intelligent automation. This new framework – built on NVIDIA Tensor Core GPUs and the NVIDIA AI Enterprise software platform for generative AI running on AWS – leverages Mavenir’s Open RAN architecture to provide accessibility into multiple open interfaces that can deliver the data needed to train and optimize domain-specific telecom LLMs.
Mavenir’s Chief Technology and Strategy Officer Bejoy Pankajakshan commented: “Our new Operations Co-Pilot framework has the potential to be a game-changer for operators, delivering a wealth of fault prediction and root cause analysis capabilities with AI-powered accuracy and speed. This industry-first solution is built on the transformative foundation of NVIDIA GPUs operating on AWS and enabled by Mavenir data, which can be accessed via numerous interfaces in the Open RAN and in the Packet Core for complete end-to-end visibility.”
He added: “The three key use cases of Core Dump Analysis, Log Similarity Search feature and Log Anomaly Detection can be used together to maximize the automated efficiency gains. Combining information from these trained LLMs will provide broader and deeper coverage of all fault and anomaly scenarios, enabling very early prediction of potential problems in the network. Moreover, as these solutions evolve, the models have the ability to continuously learn and optimize based on user feedback and iterative training with further logs, KPIs and traces, promising even greater gains.”
“In today’s fast-paced digital landscape, generative AI is a force multiplier for enterprises everywhere,” said Chris Penrose, global head of business development for telco at NVIDIA. “Mavenir’s framework, built on the NVIDIA AI Enterprise platform for streamlining the development and deployment of AI, will unlock a new level of operational efficiency for communications service providers.”
Notes to editors: Watch the video overview: Mavenir’s Operations Co-Pilot for RAN Service Assurance (RSA)
About Mavenir:
Mavenir is building the future of networks today with cloud-native, AI-enabled solutions which are green by design, empowering operators to realize the benefits of 5G and achieve intelligent, automated, programmable networks. As the pioneer of Open RAN and a proven industry disruptor, Mavenir’s award-winning solutions are delivering automation and monetization across mobile networks globally, accelerating software network transformation for 300+ Communications Service Providers in over 120 countries, which serve more than 50% of the world’s subscribers. For more information, please visit www.mavenir.com
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