AI & ML Engineering

Improving quality and preventing costs by using the power of data

Smarter through patterns

From unstructured data to business value

Few are unfamiliar with AI and machine learning. Implementing predictive maintenance and automatic quality inspection can be huge for your business. But getting started with AI and machine learning requires specific knowledge, skills and a plan. Otherwise, there is a good chance that you will get caught up in an endless web of data and algorithms. Provided it is used correctly, you can predict maintenance and reduce maintenance costs by structuring data well and building the suitable models. How do you start implementing AI and machine learning in an industrial setting? Check out the articles and talk to one of our experts.

Samantha Verkouteren

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Automated search for a needle in a haystack

Creating a Predictive Maintenance solution in the world of pipelines

Geautomatiseerd zoeken naar een naald in een hooiberg

The largest refinery in Europe is located in Rotterdam, making it one of the largest in the world. On the 550 hectare site (1000 football fields) there are about sixty factories in which oil is processed in all kinds of ways. Besides the factories, there is also an immense amount of pipelines to transport the products. In total, this involves 160,000 kilometers of pipeline, which is four times around the earth. To check it regularly for rust and wear, among other things, is an enormous challenge. And artificial intelligence and machine learning offer an answer to that challenge. Predictive maintenance using AI and ML should ensure that the maintenance of those many thousands of kilometers of pipeline must become easier, cheaper and safer.

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From unstructured data to business value for manufacturing

Our AI & ML heroes


Kennon Rodrigues

Data Engineer


Anastasiia Havriushenko

Machine Learning Engineer
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