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Neural Concept Shape: 3D Deep Learning for Enhanced Engineering

Machine Learning from experienced simulation engineers, to guide designers faster towards radically better concepts

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WHY NCS?
Product performance
By learning from any non-parametric 3D design, NCS has a tangible impact on optimization possibilities and therefore on competitiveness.
Time to market
3D Deep Learning empowers engineering organizations to achieve faster time to market and reduce response times.
Continuous improvement
Past engineering practices are under-exploiting their CAE and CAD tools and the data produced. NCS is a learning system that gets fed by your everyday raw CAE and CAD data.
World Record Holder in two Categories for Human Powered Vehicle Speed. 138 km/h Designed with NC Shape.
HOW DOES IT WORK?

NCS: one predictive model, two products

Predictive models are used to simplify processes and emulate simulation engineers' expertise, by transferring it to design engineers early in the development process.
COMPATIBLE CAD
FORMATS
ROI TIMELINE

Return on investment in just two months

After 2 weeks:

You have a clear and realistic vision for your 3D Deep Learning deployments. You start executing.

After 1 month:

Your Expert engineers have caught up with the state‑of‑the‑art.

After 2 months:

First success with measurable technical benefits.

After 4 months:

While the first team of users is already obtaining RoI, you are expanding to other teams.

After 1 year:

The benefits of these methodologies are widespread in the companies. Teams of Experts are fully independent, proposing solutions to evolving challenges.
OUR PRODUCTS
NCS Production
Massive power harnessed in an accessible design engineering toolkit
Explore NCS Production
NCS Expert
The power of 3D deep learning rethought for advanced CAE or optimization experts
Explore NCS Expert
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Design Optimization of Heat Exchangers

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A Novel Approach to Turbulence Model Development using Neural Concept Shape

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E-Drive Housing Designs Optimized using Neural Concept Shape

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NCS to Enhance the Design of Turbomachines

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Deep Learning-based Models for Fast Evaluations of Airfoil Performances in Transonic Flows

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Break the trade-off between product quality and development time

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