Perfect Match: AI meets IoT

AIoT Benefits EN
Bringing intelligence to your production

Are you looking to push the quality of your products to the top, make your processes more efficient, reduce rejects and failures and increase profits in the process? If so, it’s time for you to start thinking about the smart factory. 

Thanks to our innovative combination of AI + IoT, resulting in Artificial Intelligence of Things (AIoT), we are able to assist companies in optimizing their manufacturing and operating processes holistically and sustainably. We call this: Intelligent automation.

Need concrete examples?

Read our whitepaper to learn how companies in the pharmaceutical, energy and paper production industries are seizing an opportunity for greater efficiency, quality and revenue thanks to AIoT. Take inspiration from sensor manufacturer JUMO, which itself has succeeded in increasing the proportion of its “highest quality” sensors by 8% – the equivalent of a 20% improvement in quality.


Your opportunities with AIoT

25% increased

through AI-based process and quality improvement using the example of a car manufacturer (source: IBM)

5-20% lower labor costs

for quality control with AI using the example of an electronics manufacturer (source: IBM)

3-30% higher production efficiency

thanks to intelligent automation with AI + IoT = AIoT (source: McKinsey)

Use Case

A leading German automobile manufacturer set the goal of ensuring smooth production processes through Condition Monitoring and Predictive Maintenance. The aim was to minimize downtimes and prevent potential machine failures early on. 


Using a Data Lakehouse platform by Databricks, Device Insight developed and integrated an innovative Anomaly Detection function into the previously established IIoT solution. Parameters such as the motor temperatures of industrial robots are monitored, which can be predicted using statistical regression models. Thanks to Databricks’ cloud service, these regression models can be scaled effortlessly, training over 60,000 models simultaneously. Moreover, the anomaly detection can be performed in a few minutes across the entire fleet of machines. If deviations from the predicted motor temperature occur, the system notifies on-site staff.


What does an AIoT project look like?

You don’t know where your greatest potential lies or if your data base is sufficient? No problem. We will advise you right from the very first idea phase, screening your processes for possible optimization. Our integrated AIoT approach comprises a total of 5 steps with which we accompany companies on their way to intelligent production – away from individual solutions and towards a holistically optimized smart factory.

Become an AIoT pioneer
Martin Dimmler
Martin Dimmler
AIoT contact

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