Tech Mahindra has announced a new multi-modal network operations large language model for telcos, developed using the NVIDIA AI Enterprise software and AWS Cloud infrastructure. The model is based on Llama 3.1 8b instruct model and is heavily customised for telecom networks, by training on large network datasets and applying the latest generative artificial intelligence (GenAI) and agentic AI frameworks. It is designed to manage vast structured data (events, alarms, counters), unstructured data [logs, methods of procedure (MOPs), standard operating procedures (SOPs), images, text, marketing], and all relevant network data, allowing proactive issue resolution and enhanced service quality.
This model enables the transformation of traditional telecom networks into fully autonomous networks [layer 4 (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. Tech Mahindra, working 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 brings together Tech Mahindra’s network automation platform, netOps.ai, Tech Mahindra Optimised Framework TENO that incorporates NVIDIA AI Enterprise software, including NVIDIA NeMo and NIM microservices, along with AWS’s Amazon Elastic Container Registry (Amazon ECR), Amazon Elastic Compute Cloud (Amazon EC2), and Amazon Elastic Kubernetes Service (Amazon EKS). This model empowers telecom operators to transform their networks into intent-based networks, embodying the principles of self-driving networks (Zero x and Self x).
In the initial phase of the development, the multi-modal network operations large model will prioritise improving operational efficiency through “Intelligent Observability”, introducing two critical 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. Complementing this, the second use case, Proactive Network Anomaly Resolution Hub, will be an advanced AI-powered auto-resolution system that will autonomously detect and resolve network anomalies such as alarms or events with zero human intervention.
Additionally, the solution architecture will seamlessly integrate AI-driven intelligence into network operations, encompassing three key components including first efficient data ingestion from the network; second, data curation and model customisation to enhance AI training; and third, automated action implementation for quick resolution and restoration of services.
Commenting on the announcement, Manish Mangal, chief technology officer, telecom and global business head, network services, Tech Mahindra, said, “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.”
Meanwhile, Chris Penrose, vice president, 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.”
