Shape: Deep learning for enhanced engineering

Machines, learning from elite simulation engineers, to guide designers faster towards radically better concepts

Why shape?

Product performance

By learning from any non-parametric 3D design, Shape has concrete effects on optimization possibilities and therefore on competitiveness.

Time to market

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. Shape is a learning system that gets fed by your everyday raw CAE and CAD data.

Human Power Vehicle Speed World Record Holder in two Categories. 138 km/h Designed with NC Shape

Shape: 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.

CAD tool integrations

ROI Timeline

Return on investment in just two months

After 2 weeks:

You have a clear and realistic vision for your Machine 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