We automate Computer Aided Engineering (CAE) processes to an unprecedented degree. Our technology streamlines simulation-driven product development and unlocks the potential of CAE for medium sized enterprises.
Computer Aided Engineering makes use of numerical simulations to predict the physical behaviour of products or processes. The numerical analyst is the heart and soul of simulation-driven development. Drawing on his expert knowledge and armed with expensive software he puts a lot of manual effort into running simulations that help engineers to understand and optimize the performance of their designs. Our machine learning platform along with our open source middleware helps numerical analysts to automate their simulations and to collaborate efficiently with design teams.
Automate geometry cleaning, mesh segmentation or re-meshing tasks with our machine learning framework.
Build powerful CAE workflows quickly and easily by combining established CAE modules with in-house technology and open source software.
Use web-based interfaces to track simulation results and to communicate and share files with other team members.
Our middleware framework will be available as open source software. Easily develop your custom solutions on top of it at zero license cost.
Keep it simple
Our APIs and user interfaces are built for maximal simplicity. Existing workflows can be migrated within days.
From large enterprises to small CAE consultancies, from workstation based simulations to cloud based CAE workflows: Our solutions adapt seamlessly.
Numerical Analysts can spend less time on routine tasks like re-meshing, data integration and scripting and more time on real modelling and analysis.
Design Engineers can iterate designs quickly by running simulations directly in the browser and collaborating closely with numerical analysts to interpret the results.
CAE Executives can easily establish CAE best practises, reduce manual effort and cut license costs to develop better products faster and cheaper.
Renumics emerged from the Karlsruhe Institute of Technology (KIT) in 2016. Our team has extensive hands-on experience in the realm of CAE and software engineering as well as a strong research background in numerical simulation and cognitive computing.