Engineer looks at the aiomatic dashboard.

Predict your machines' health with one software

Are your machines & production processes ready for the future?

Manual machine monitoring: Inefficient, risky, expensive
Decentralized data collection and delayed analyses often result in problems being identified too late. Unplanned downtime is now costing the 500 largest companies in the world 11% of their turnover (Siemens 2024).
Monitoring with aiomatic: simple, precise, efficient
Our software collects machine data independently of the manufacturer in a live dashboard. Thanks to AI-based analyses, you can identify errors early on, prevent failures & optimize machine performance.
Image of Lena Weirauch with a quote.

"Companies in Germany must future-proof their production now to stay competitive. Only 1.4% of GDP is invested in digitalization, leaving Germany far behind in an international comparison."

Lena Weirauch, CEO & Co-Founder of aiomatic
Photo: Henning von Holdt

Stay ahead with AI — because stagnation is not an option

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Dashboard that shows the health status of the machines

Our SaaS solution for Predictive, future-oriented Maintenance

Our software does not only monitor the current status of machines, but also uses AI and data analyses to precisely predict future failures. With the help of a Health Score between 0 - 100 % developed by us, you can identify errors at an early stage and plan maintenance processes optimally.
Early detection of anomalies and faults
Comprehensible health prediction
Visual analysis to identify the causes of failure

Explanation of our Predictive Maintenance software

For which target groups is our software suitable?

Regardless of whether you build or operate machines — our software adapts to your needs. We have extensive experience with digitization projects in the pharmaceutical, energy, food, manufacturing, automotive and mechanical engineering industries.
Efficient monitoring of a machine.

Medium-sized manufacturing companies

Do you want to use your machines more efficiently without starting a major IT project right away? We will guide you step by step and start where your company is today. With clear instructions, structured onboarding and regular exchange, the implementation can be planned rather than complicated.
Complex machine from the automotive industry.

Large-scale industrial companies

Monitoring your machinery is complex and failures can cause major losses? Our software protects your critical operations. With state-of-the-art encryption and GDPR-compliant architecture, we ensure the highest level of cyber security - without turning your infrastructure upside down.
Complex machine being monitored.

Machine manufacturers from all industries

With our software, you can offer your customers greater reliability and predictable maintenance. This increases customer satisfaction and lowers warranty costs. At the same time, you increase your after-sales turnover by offering spare parts and services exactly when they are needed.

Project Process: As simple as possible

Increasing efficiency in three steps: Together, we analyse your requirements, select a suitable solution package and seamlessly integrate our software into your processes. Transparent milestones and our experienced team will guide you on your way to success.
Technical employee standing next to a machine.
Interface of the software as an image.

Safely implemented & ready for immediate use

Thanks to standardized interfaces such as OPC UA, you can easily connect our software to your machines and IT systems — without complex IT projects or expensive hardware investments. Of course, your data is in safe hands with us: It is stored in the ISO/IEC 27001-certified Microsoft Azure cloud and managed in accordance with the GDPR and EU AI regulation.

What are the prerequisites for you to benefit most from our solution?

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High level of digitization of your machines as well as a secure and scalable data infrastructure.
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Reliable sensor data that allows conclusions to be drawn about the status of the systems.
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Machine data is digitally recorded periodically or on an event-driven basis at least once an hour.
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