Solve problems before they become problems

Upgrade your systems with predictive maintenance and resolve issues before they have the chance to interrupt service or availability. Predictive maintenance will improve the reliability of your program while reducing maintenance costs by up to 35%.

Key Features

Anomaly detection

Our predictive maintenance software recognizes correlations, relationships and similarities between data. It can detect problems or anomalies in the service delivery chain and deliver recommendations for the teams responsible for service availability and quality.

Real-time action

Once a situation or anomaly is detected, immediate action can be taken to prevent availability issues or bad quality service. Our software acts in near real-time.

Monitoring and analysis

Our software makes it easy for you to monitor and analyze data from the systems, and to identify irregularities in the data set. Reporting modules and interactive dashboards allow for easy and effective analysis of root causes and maintenance effectiveness.

Continuous learning

To stay ahead of the curve and ensure the most accurate insights, our predictive models are continuously being retrained on the most recent data available.


Significant operational cost reduction

Predictive maintenance promises cost savings over preventative maintenance because tasks are performed only when warranted. While preventative maintenance relies on statistics to predict when maintenance will be required, predictive maintenance relies on the actual condition of the equipment.

Business-focused assurance

Predictive maintenance allows convenient scheduling of corrective maintenance and prevents unexpected system failures, thus reducing the overall number and severity of alarms and incidents all while increasing your operational efficiency. This solution allows for the preservation of knowledge in the event of staff changes, which means lower entry costs for new employees and an overall higher quality of service.

Improved customer experience

Create the best possible experience for your customers by improving network and service quality, reducing service restoration time, increasing service availability, and reducing churn rate.

Use Cases

Predictive maintenance is a sophisticated approach to autonomous service delivery and assurance. Predictive models based on deep learning technology prove effective as they can follow complex, non-linear relations within the data, as well as discover new schemes. Nevertheless, no single model or combination of similar models can detect anomalies effectively. Different kinds of models are often used together to obtain a higher level of predictive maintenance. Given the widespread use of AI across various applications and its black box nature, explainability  in artificial intelligence (XAI) is one of the problems at the forefront of AI research. Predictive maintenance allows the generation of explanations for decisions made by the software.

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