Our mission is to bring Machine Learning &
AI solutions to

Increasing safety, sustainability and efficiency

About us

MoorInsight, founded in 2016, is specialized in sensor technology and intelligent algorithms for the maritime and process industry. Combining data science skills with in depth knowhow of sensoring and domain knowledge makes us unique.

Our team consists of highly qualified, experienced industry professionals with a solid track record in their domain. With our in depth knowledge of sensoring, data communications and analytics, our team is able to quickly and accurately create solutions to suit a broad range of business.


MoorInsight provides predictive analytics for streaming machine-generated data. It offers a platform that makes it easy for individuals to use machine-learning algorithms to classify streaming data from applications, devices, and sensors. The company’s platform is used in a variety of industries to extract actionable insights from streaming data generated by devices and sensors.

  • Scalable
  • Secure
  • Open standards
  • Custumizable (Flexible IT)


Technology consultancy

MoorInsight offers technology consultancy services in the areas of measuring and data analysis. Our expertise ranges from robust data acquisition, statistics and data science to generate customer insights, creating value, developing new concepts and realizing products 


In our projects we closely work together with our clients to achieve the optimal result.

Use cases

Some examples of our projects:


We collect data from smart devices and existing diagnostic systems. After applying our algorithms, we are able to identify issues, deviations and optimizations. Always keep in mind the end goal for the client: better performance, reduced downtime and lower operational costs. MoorInsight also provides own portable tools and sensors to do extra measurements.

Autonomous vessels

MoorInsight is involved in several autonomous vessel projects. In these projects our goal is to make safe and efficient autonomous vessels possible.

De Lerende steen

Involved in a project that optimizes waste-to-energy plants. One of the deliverables is a digital twin of the waste incineration plant. Using this dynamic simulation model the processes in the plant can be simulated and visualized. The developed algorithms can also be used for monitoring and predictive maintenance.