Predictive maintenance for digital services

Offer valuable and actionable insights to your customers on what needs to happen when - and ultimately improve their asset performance.
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Generating valuable insights based on machine data is hard.

Are your customers demanding more than just a dashboard reflecting their machine data? OEMs are struggling with selling their digital products on top of their machine portfolio. Why? Getting valuable insights out of your customer’s machine data is expensive and hard to scale.

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Start selling your machine insights.

Get closer to your customers by offering data driven insights that drive uptime and asset performance. Digitise and scale your asset knowledge with our Asset Insights solution.



Transform data into insights

Link patterns in your available data to actions via labelling. Reuse the created labels every time the same pattern occurs to reduce time to diagnose and never miss issues again.

Monitor the quality of your intelligence portfolio

Know how well each algorithm is performing to be able to decide when to push it to your customers.


Train, run and manage your AI

Having many digital services for your clients can be cumbersome. We manage all your intelligent components for you ensuring the highest possible performance, endless scalability and automated retraining.

Train

Automatically re-train algorithms based on performance.

Run

Deploy a new algorithm version in under 10 minutes and run them automatically.

Manage

Get continuous insight into performance, easily make changes to (a subset of) algorithms if required.

Together with Quinyx, Evos Amsterdam is making the shift towards preventive maintenance by interpreting data from our 1300+ motor operated valves via intelligent algorithms. This will help us to see faults coming, reducing business failure costs and avoiding safety & environmental critical incidents.
Christiaan Kop
Technical Manager Evos

Get in touch with an expert

Reach out to one of our maintenance experts for a free demo of one of our solutions.