Maintenance of corporate assets is an important task to assure availability and to maintain total cost of maintenance at reasonable levels.

Many times maintenance is a shared task between different departments and between internal staff and external providers. The right planning of maintenance visits and efforts is a complex task. On one hand the workforce has to be used in a smart way to anticipate the optimum moment to realize maintenance. The optimum moment is close to the moment when an asset breaks and not to early to assure maximum availability.

With our AI based maintenance incidents predictor the workforce and maintenance planning can be improved significantly. What we do is learning from your past incidents to predict future incidents. The result is an API you can use to connect with your workforce system to improve planning. With the update information our AI algorithm will be trained frequently.

Every company with corporate assets deployed in different locations and with the need to optimize maintenance efforts and effectivity can benefit from our incident predictor. Our flagship customer is a multi-national telecommunications company using our API to predict and improve the management of EHS incidents.

Getting started with our AI based maintenance incidents predictor is easy:

1) Testdrive

-Upload your past incidents data

-Train the model

-Review the trained model

-Evaluate ROI

2) Production

-Activate API

-Consume API

-Retrain model

During the Testdrive your data will be evaluated and the impact of the trained model will be tested. If the result is favorable go-live of the service will be recommended.

Virtual AI based incident auditor

durch Enzyme