Technology consulting and digital solutions company Tech Mahindra has developed a new Multi-Modal Network Operations Large Language Model to help telecom operators leverage artificial intelligence (AI) for automating network operations. The model was developed using Nvidia AI Enterprise software and Amazon Web Services (AWS) cloud infrastructure, along with Meta's Llama 3.1 8b Instruct model. The company said it has "heavily customised" the model for telecom networks, by training on large network datasets and applying the latest generative AI and agentic AI frameworks.
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Multi-Modal Network Operations Model
The model is designed to manage vast structured data (events, alarms, counters), unstructured data (logs, MOPs, SOPs, images, text, marketing), and all relevant network data, allowing proactive issue resolution and enhanced service quality. Tech Mahindra said on Tuesday that the model enables the transformation of traditional telecom networks into fully autonomous networks (L4 and above).
While telcos have been implementing AI use cases with a transactional approach, achieving true operational efficiency requires a holistic embedding of AI capabilities within the network, the company noted.
Collaboration with Nvidia and AWS
Tech Mahindra emphasised that its collaboration with Nvidia and AWS is "facilitating this transition and helping the telecom industry harness the full potential of AI for enhanced performance and operational excellence."
This collaboration integrates Tech Mahindra's network automation platform, netOps.ai, with the Tech Mahindra Optimised Framework (TENO), which incorporates Nvidia AI Enterprise software, including NeMo and NIM microservices. Additionally, it utilises AWS services such as Amazon Elastic Container Registry (Amazon ECR), Amazon Elastic Compute Cloud (Amazon EC2), and Amazon Elastic Kubernetes Service (Amazon EKS).
Key AI-Driven Use Cases
In the initial phase of the development, the new Model will focus on improving operational efficiency through "Intelligent Observability," introducing two key AI-driven use cases.
First, the Dynamic Network Insights Studio will provide a unified 360-degree AI-powered network observability solution, offering deep insights into network performance for AI teams, network operations, and C-suite executives.
The second use case, Proactive Network Anomaly Resolution Hub, will be an AI-powered auto-resolution system that will autonomously detect and resolve network anomalies such as alarms or events with zero human intervention.
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Impact of AI on Telecom Network Management
"The shift towards autonomous networks has become imperative within the telecom industry. Our collaboration with Nvidia and AWS is pioneering a Multi-Modal Network Operations Large Model designed to enhance security, automate network management, and improve operational efficiency. Through this work, we will empower telcos to reduce operational costs and pave the way for a more agile and resilient network environment," said Manish Mangal, Chief Technology Officer, Telecom and Global Business Head, Network Services, Tech Mahindra.
Chris Penrose, Vice President of Telco Business Development, Nvidia, said, "The introduction of large telco models that understand the network language is a transformational moment for the telecom industry, helping to deliver AI-accelerated operations. Large telco models like Tech Mahindra's new Multi-Modal Network Operations Large Model — based on Nvidia AI Enterprise — offer the foundation for creating multiple AI agents that will help enable fully autonomous networks."
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Vision for AI-Driven Telecom Innovation
With global AI spending in the telecom sector reaching multi-billion-dollar investments, this collaboration underscores Tech Mahindra's commitment to driving AI innovation in telecom and redefining network operations through intelligent automation, deep learning, and multimodal AI models, the company highlighted.
Beyond this collaboration, Tech Mahindra said it is also leveraging the Multi-Modal Network Operations Large Model for other business use cases.
