AI & ML Engineering

Improving quality and preventing costs by using the power of data

Smarter through patterns

From unstructured data to business value with the use of AI & Machine learning engineering

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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An efficient infrastructure for KLM’s predictive models

Data and self-learning algorithms support KLM’s operational decisions.

KLM’s Operations Decisions Support is the department responsible for processing all operational information to produce valuable forecasts. Part of this is done through self-learning algorithms, part of various predictive models that know a range of end users. KLM called in LINKIT to ensure that these algorithms can be used correctly and have this knowledge in-house for the future.

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From unstructured data to business value for manufacturing

Our AI & ML heroes

Data engineering & AI


Kennon Rodrigues

Lead AI & Data Engineering