How Swisscom is Using AI to Simplify Network Management and Enhance Efficiency

Network Management Challenges

Managing large-scale networks is no easy task, especially for telecom companies that deal with massive amounts of data every day. For Swisscom, the leading telecommunications provider in Switzerland, this challenge was becoming increasingly complex. Their network engineers were spending a significant amount of time gathering and analyzing data from various systems just to keep things running smoothly. This routine work not only consumed valuable hours but also left less time for more strategic and innovative tasks. To address this, Swisscom turned to artificial intelligence (AI), aiming to streamline operations and reduce the burden on their technical teams.

Introducing the Network Assistant

The result of this effort is the “Network Assistant,” a new AI-powered tool built using Amazon Bedrock, a cloud-based platform that supports generative AI applications. The assistant helps engineers quickly access and interpret network data by using natural language queries—meaning they can simply ask questions in plain English (or any supported language) instead of digging through multiple systems or writing complex code. Behind the scenes, the system uses a method called Retrieval Augmented Generation (RAG), which first finds relevant information from Swisscom’s internal knowledge base and then generates accurate responses using a large language model.

Handling Diverse Data Types

What makes this assistant particularly useful is its ability to handle both structured data—like tables filled with performance metrics—and unstructured documents such as manuals or configuration guides. Over time, Swisscom refined the system to be more precise in how it retrieves and processes information. They introduced specialized “agents” within the assistant: one focuses on documentation, another handles calculations, and a supervisor agent coordinates between them. This setup allows engineers to get detailed answers about network health, performance indicators, or troubleshooting steps without switching between tools.

Scalability and Security Features

One of the key strengths of this solution is its scalability. As Swisscom’s needs grow or change, the system can adapt by adding new capabilities or integrating with other internal systems. It also maintains high standards for data security—a critical requirement in telecommunications—by filtering out sensitive information and blocking potentially harmful inputs. These safeguards help ensure that both customer privacy and operational integrity are protected.

Aligning with Digital Transformation

Looking at Swisscom’s broader strategy, this move aligns well with their ongoing efforts to modernize operations through digital transformation. In recent years, many telecom companies have been exploring AI to improve customer service or optimize infrastructure management. For example, Swisscom has previously adopted cloud-based analytics tools and automation frameworks to enhance service reliability. The Network Assistant builds on these foundations but takes it further by introducing conversational AI into day-to-day engineering workflows.

Supporting Professionals with AI

This development also reflects a growing trend among global tech companies: combining traditional data processing methods with newer AI techniques to solve practical business problems. Rather than replacing human expertise, tools like Swisscom’s assistant aim to support professionals by reducing repetitive tasks and improving decision-making speed.

Insights for Future Applications

In summary, Swisscom’s Network Assistant shows how generative AI can be applied thoughtfully in a highly technical field like network operations. By choosing Amazon Bedrock as its foundation and focusing on real-world challenges faced by engineers, the company has created a tool that improves efficiency without compromising accuracy or security. While still evolving, the assistant already demonstrates strong potential for scaling across different teams and use cases within Swisscom.

Takeaways for Organizations

For readers interested in how AI might help their own organizations—especially those dealing with complex systems or large volumes of data—Swisscom’s approach offers some useful insights. It highlights not just what’s possible with today’s technology but also how careful planning and gradual improvements can lead to meaningful results over time.