Our mission is to empower everyone to unlock their full potential from themselves

The best of human and machine

We believe that everyone – especially you – should have the opportunity to reach the full potential and focus on where the strengths are. From our point of view, this can only succeed if people concentrate on their abilities and are supported by machines in the best possible way. In our view, the strength of people is their creativity, and the strength of machines is their ability to quickly combine complex data and find solutions. If you combine these two components and let human and machine work together, data becomes useful. With this vision and our motivation, we want to enable you to get the best out of yourself and to actually benefit from your strengths.

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From science to practice & from practice to science – that's what we believe in and that's what we're working on!

  • Research-based know-how
  • Training experience
  • Existing and new data
  • Physiological expertise
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    Make objective decisions

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    Putting research results into practice

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    Make decisions based on scientific evidence

Leadership through artificial intelligence

With the help of data intelligence, the mass of collected data can be processed and interpreted by means of artificial intelligence and made into concrete training recommendations. Insights are gained from unused raw data that were previously not available.

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    Data analysis

    In data analysis, useful and consistent information is gained from collected data by using certain statistical methods.

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    Data Intelligence

    The information gained from data analysis is handled in a value-added-oriented manner by using data intelligence. Accumulating data is systematically collected and managed, the information is usefully processed and intelligently exploited. In this way, added value is generated from the data.

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    Machine Learning

    The “artificial” generation of knowledge from experience is called machine learning. During the learning process, algorithms build up a statistical model from examples and training data, whereby patterns and regularities are recognized, so that even previously unknown data can be assessed.

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