PI Probaligence Gmbh


31.01.2024, When selecting a network partner for AI, PI Probaligence GmbH quickly emerged as the perfect option for CADFEM and the requirements identified by CADFEM customers. The primary deciding factors were:

  • the clear focus of PI on ML in combination with effective stochastic methods
  • the PI philosophy of close integration of innovative research and industrial practical relevance, which suits CADFEM
  • the unique PI algorithm STOCHOS, which combines expert independence, efficient utilization of computing resources, and high quality results.

Thanks to the combined approach of neural networks and Gaussian processes, STOCHOS offers outstanding prediction accuracy even with a small database. STOCHOS is also characterized by its ability to reliably evaluate real and noisy data from a wide variety of sources, including measured values, simulation results, and relevant key figures, and even combine them in a meaningful and resource-efficient way.

Last but not the least, the already existing proximity of PI to simulation is another strong argument. On the one hand, PI already works together with ANSYS, Inc. and on the other hand, the founders of PI are very familiar with simulation methods due to their previous professional and scientific activities.

By acquiring a stake in PI Probaligence GmbH, the CADFEM Group has further expanded its family of solution partners who combine important megatrends with the field of simulation within the global network.

By working with PI, we are able to offer our customers comprehensive expertise in AI. PI will also help us to supplement established simulation methods with AI technologies. One conceivable application example is simulation-based digital twins. With ML, the computing times for the models can be reduced to a fraction of the usual time, meaning they can be carried out almost in real time.

Dr.-Ing. Christoph Müller, Managing Director at CADFEM International GmbH

The possibilities of AI for simulation are immense, for example for additional product optimization, digital twins or autonomous decision-making processes.

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