Empower process and asset experts with advanced analytics to Analyze, Monitor and Predict the operational performance of batch, grade and continuous manufacturing processes.


More and more data is being gathered daily from instruments, sensors and devices.

How can you turn real time data into real time performance optimization?


Advanced analytics requires expert knowledge of the asset and process behavior.

Is it really necessary to build complex data models for every case?


Process engineers are not data scientists, and vice versa.

Can you empower process and asset experts with analytics to let them help transform your business?


Improving profitability requires acceleration of change.

How can you quickly embed an advanced analytics solutions in your organization and successfully manage the change?

Process Engineer 4.0

To benefit from the full potential of industry 4.0, process and asset experts must be empowered with analytics to answer their own day-to-day questions. With use of our self-service advanced analytics solution, process engineers will move from analytics aware to analytics enabled up to analytics expert. The new Process Analytics Engineer will be better equipped to improve overall equipment effectiveness, improve product quality and reduce costs.

Self-service Analytics


Classical model-based predictive analytics typically require expensive projects and data science expertise. For many analytics questions it is faster and more efficient to use a self-service analytics tool, designed with operational end-users in mind. Robust algorithms and familiar interfaces maximize ease of use for non-data scientist users. As a result, many cases to optimize the operational performance of the plant can be handled by the people who can really interpret the data.

Actionable Intelligence

TrendMiner reads all the industrial data generated by your production processes (time series data from sensors, instruments and assets). This big data can then be analysed to identify trends and create actionable information to solve production issues. Users can troubleshoot problems and monitor processes and assets in real-time to make better decisions, faster.