Engineering Intelligence

Breaking the trade-off between product quality and development time, using 3D Deep-Learning algorithms.

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OEMs and Tier 1 in the automotive & aerospace industries are currently having to transition to new type of products and components. Trends such as vehicle electrification are forcing this transition hence creating a need to drastically increase the speed and the efficiency of the product design development.

Performance early-on

Unlock 2030 technologies today

The product is optimized very early on, which results on best-in-class performance and reduced late stage failures. Design engineers are guided to create products beyond what is normally achievable with conventional design tools.

Speed-up product delivery

>90% lead-time reduction

By having access to physics simulation results in seconds instead of hours or days, CAD teams can iterate at a significantly faster pace than today. It makes them operate more efficiently with CAE teams, reducing drastically the iteration time between the different teams. The project or RFQ is then completed much faster.

Leveraging competencies

CAD team operational twice faster

Design engineers are better guided in their choices by the algorithm and therefore need less intuition about the product and less trainings. This reduces substantially the involvement and time from the CAE team. Consequent cost savings are achieved through the efficient use of resources and competences.

actual examples from customers' success stories

Neural Concept Shape (NCS) provides physics-related insights directly from the CAD tool and guides the designer towards better performance

No more meshing, no more waiting, no more failures.

Customer & Partner Stories

Break the trade-off between product quality and development time

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