The no. 1
From data to access – If you are looking to optimise your production planning, asset management, predictive maintenance or connected product development, digitalNXT will help you kick-start your digital transformation.
Data for smart prediction
The scales used at PostNL’s service points, Remeha’s boilers and BAM’s asphalt damage inspection all have one thing in common: DATA! We combine and analyse all data on our platform using AI algorithms for predictive maintenance. We then use this data to perfect your planning, taking into account external factors such as weather and peak times, like orders placed in the run-up to certain public holidays or other special occasions.
4C-model
Digital Transformation. It is happening all around the world. Perhaps you’re thinking about it too? Good news! You can start tomorrow. We have developed a model that digitally transforms any company in 4 steps.
Watch the animation!
Four easy steps
Each business case is unique, but the underlying processes to ensure successful results are quite similar and always contain these four steps:
2. Prove business value
in pilot projects
Our comprehensive platform-as-a-service facilitates fast, secure and scalable implementation of the business cases outlined in step 1 as part of a 20-day challenge. This allows you to invest in the added value of the business case instead of in the underlying technology.
3. Become a data master
The driving factor behind every successful business? Data! Insights gathered in step 2 typically generate new ideas and business cases. We use artificial intelligence (machine learning and deep learning) in a variety of data to enable you to discover entirely new links. And you can effortlessly add new data sources, including weather and traffic forecasts, and use this data to further improve your planning process. Your data scientists, analysts and developers can count on our expertise to help them develop their solution on our platform, either by developing custom applications or through integration with existing applications or data flows.
4. Transform into a digital business
Setting up one or several pilot projects and developing AI algorithms is relatively easy; the true challenge lies in implementing the new business model in the current organisation. This requires a seamless integration of the new environment into your existing IT infrastructure, which we can ensure through the implementation of a uniform, secure, model-driven architecture (Data Lake), giving users fast access to aggregate data. We enable businesses to store data of any size, shape and speed, and apply AI (machine learning, deep learning) to the data ingested. The Data Lake uses your current investments and seamlessly integrates with operational data sources and data warehouses to increase visibility across your company.
Monitoring ánd managing
Hytech uses our platform to manage and monitor its digital scales, which are located at as many as 3,300 PostNL sites.
The service engineers who install new scales and service the installed base have a mobile app that uses predictive maintenance to indicate which scales need service and when. This has led to incredible improvements: both the back-office workload and incidents have been reduced significantly.
An IOT-solution for boilers
We provided Remeha, a manufacturer of water and space heating systems, with an IoT solution that enables remote reading of boiler data.
Routine servicing can now be replaced by predictive maintenance. If a boiler does need to be repaired or serviced, the engineer can check its status on their mobile device, assess the situation and arrive on site with the right equipment and parts to fix it.
Collecting train diagnostics
International engineering and consultancy firm Ricardo Rail provides maintenance services to railway organisations including ProRail and NS Support.
Ricardo Rail contracted us to develop a platform for collecting and analysing diagnostic data. This platform enables data-driven decision-making in a wide variety of areas, such as predictive maintenance.
Automatically recognizing asphalt damage
We developed a self-learning image-recognition algorithm for construction firm BAM, which enables fully automatic identification and labelling of asphalt damage based on video images.
Inspections previously carried out by highly skilled staff who spent all day analysing video images, has now become a fully automated process, and a second opinion is now only required in the event of doubt. BAM can make sure these people are assigned more important duties that are more in line with their skills.
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