Today, the development of a new product very often involves computer-aided design (or CAD) which encompasses all the geometric modelling techniques used to sketch, prototype and virtually test the product.
Computer Aided Engineering (or CAE) uses the same process to design, simulate and approve new products and processes in the engineering sector.
However, a single CAD or CAE simulation can take hours or even days to complete, depending on the technology used. To overcome these limitations, Neural Concept has developed a deep learning software called “Neural Concept Shape” that can predict the outcome of simulations in as little as one second.
Meeting engineering challenges quicker than ever before
Using a complete archive of data from previous simulations and making the most of raw CAD and CAE data, Neural Concept Shape continuously learns and determines the optimal solution. With this software, companies can accelerate their R&D cycle, improve product performance and solve their next engineering challenges. With faster response times and shorter time-to-market, organizations can therefore optimize their production.
Located at the EPFL Innovation Park in Lausanne (canton of Vaud), the 18-people team aims to reach out to the automotive, aerospace, marine and architectural sectors.
After raising funds from the ESA Business Incubation Center, Constantia New Business and the High-Tech Gründerfonds, Neural Concept was granted a Tech Growth Loan from the FIT. This new funding will enable the company to continue the development of its product by covering the costs of R&D, cloud computing and of the proof of concept.
