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A large telecommunications provider sought to improve customer experience by making better use of its existing network and usage data. While they had access to vast amounts of information—such as internet traffic volume, duration, and connection quality—they lacked a clear understanding of user behavior and how it correlated with network performance. To address this, they collaborated with Codinix Technologies, a company specializing in Machine Learning and AI Development Solutions, to apply advanced data analysis techniques including Non-negative Matrix Factorization (NMF).
The client is a national telecom operator delivering broadband internet services to a broad user base. With millions of users and a high volume of traffic data generated daily, they needed a method to interpret usage trends, monitor service quality, and guide infrastructure investments using data-driven insights.
The project aimed to achieve several goals:
Some of the core issues identified at the start of the project included:
Codinix Technologies worked with the telecom provider to implement a structured machine learning solution. The approach included:
The solution was designed to support interpretability, scalability, and integration into existing operational workflows.
The implementation provided several insights and operational benefits:
This project highlights how Machine Learning Consulting Companies, such as Codinix Technologies, can support telecom providers in converting raw data into meaningful operational insights. By integrating Machine Learning and AI Development Solutions with performance analytics, the telecom company was able to better understand its user base, improve network reliability, and make informed strategic decisions.
Such applications of machine learning are an integral part of broader digital transformation solutions, especially in industries where real-time data and customer experience are critical to success.
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