Avanseus offers AI-Driven Predictive Maintenance Solutions for Communication Service Providers


One of the early use cases Avanseus has developed using its very own predictive models and machine learning algorithms was Predictive Maintenance (PdM) for technology infrastructure. This solution has been successfully implemented across several large Communication Service Providers (CSPs) worldwide.

CSPs are responsible for managing networks that are highly complex and dynamic, with thousands of faults and alarms that can occur round-the-clock. Network managers must conduct root cause analysis in real-time to identify and solve problems as quickly as possible, but this process can be time-consuming and challenging. To help CSPs address these challenges, Avanseus has developed PdM solutions that use machine learning algorithms to automate fault and alarm management, reducing downtime and improving customer satisfaction.


Avanseus’ PdM solutions use AI-driven applications to filter and correlate alerts based on timing, location, and relationship, providing engineers with early warnings of potential device or node failures. These applications learn from patterns over time, enabling CSPs to conduct predictive maintenance, reduce emergency support, and spare parts expenses, thus improving uptime and reducing mean time to response.

Transforming a CSP’s network operations with AI-driven applications is not a straightforward process. It involves integrating disparate applications such as fault and alarm management, trouble ticket management, and IT automation. Each of these applications must be integrated fully and tailored to the provider’s specific needs to reap the full benefits of these new transformative processes.


Avanseus has successfully integrated the solution across several CSPs’ networks and regions, and some best practices can help accelerate time to value and return on investment. Firstly, engaging a systems integration partner to provide timely first-, second-, and post-installation technical support ensures the applications are continuously learning and adapting to the dynamic network environment. Secondly, CSPs should align and document fault and alert correlation policies that meet their specific needs, improve decision-making and accelerate root cause analysis. Thirdly, having a view of the full topology of their network, including interrelations between devices and nodes, and peer-to-peer connections help to filter out critical alarms and improve fault analysis capabilities.

Avanseus’ PdM solutions include several features that can help facilitate integration, such as Cross-Domain Correlation and Fault Cluster Discovery, Root Cause Analysis, and Return on Effort, which allows CSPs to focus on a subset of predicted faults that will be most impactful on network operations.


Avanseus and its systems integration (SI) partners can help CSPs to transform their network operations with AI-driven applications, improving uptime and service levels while decreasing costs. For more information, visit our website and Linkedin page to find out how.

Contact us to schedule a consultation with our experts and learn more about how Avanseus can help transform your network operations.