n many industries today, companies are faced with the challenge of driving innovation faster without wasting time, resources or high investments in hardware. Traditional simulation processes – such as flow or process analysis – are often complex, time-consuming and require specialised expertise. This is precisely where there is a clear need: tools that deliver simulation results with minimal effort and maximum significance are crucial for reducing development times and making informed decisions. At the same time, there is growing pressure to work in a more sustainable, cost-efficient and agile manner – without relying on expensive infrastructure.

With StrömungsRaum, IANUS Simulation addresses this need directly: According to its developers, the cloud-based platform combines state-of-the-art technologies such as high-performance simulations, generative AI and machine learning to efficiently optimise industrial processes – without additional hardware investments. Users benefit from fully automated pre-processing, intuitive operation even without in-depth technical knowledge, and real-time visualisations that enable quick decisions. The platform is scalable, cost-efficient and can be flexibly integrated into existing systems, making it a forward-looking solution for a wide range of applications. Whether optimising injection moulding or hot runner processes or analysing complex flow phenomena, StrömungsRaum is designed to help identify errors at an early stage and significantly accelerate development cycles.

IANUS Simulation itself is a deep tech company founded in 2006 and based in Dortmund, Germany, which specialises in the digitalisation, automation and optimisation of industrial processes through simulation and artificial intelligence. The company combines cutting-edge academic research with practical application and, according to its own statement, operates one of Europe's largest networks of experts in the field of simulation technology. With solutions such as StrömungsRaum, IANUS aims to enable companies of all sizes to operate more competitively and innovatively by replacing time- and resource-intensive trial-and-error approaches with precise digital twins.

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