We have set ourselves the goal of advising and supporting companies in the process of digitization. All relevant data of your company will be sifted and digitized by us. Your business processes are analyzed and optimized.
Our AI systems are then used to monitor your data and processes. AI provides you with a continuous flow of information and analysis in real time. It monitors and alerts when data or processes deviate and shows recommended actions.
As costly and disruptive as the digitization of business processes is – there is no alternative to achieving higher efficiency, productivity and better performance at lower costs!
It is important to start with the analysis of the initial situation. Only then can concrete digitization goals with high and individual value be defined. Production-specific key figures and industry-specific analyses can then be used to evaluate which measures are target-oriented. Because digitization is very individual and every implementation roadmap is different! It is essential to know before the start of the project which key figures correspond to the achievement of objectives.
Perhaps a detection rate of 80 percent is already enough to achieve a worthwhile optimization. And perhaps achieving 98 percent is neither necessary nor economical.
In our experience, data availability, quantity and quality are often the biggest challenges at the start of digitization. Even though many opportunities result from the fact that automation and digitization generate much larger volumes of data – unfortunately, these are often available on different, separate systems or in incompatible standards.
Digitization and AI give production powerful tools to increase efficiency, optimize manufacturing processes and produce closer to the market. AI can bring about amazing progress through better and deeper data analysis as well as pattern/anomaly recognition and machine learning – for example, when it comes to optimizing processes in manufacturing, organization and logistics, reducing waste and energy consumption, or increasing quality and sustainability.
Efficiency improvement.
Real-time data analysis.
Cost savings.
Improved quality.
Customer focus.
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