An Artificial Intelligence Algorithmic Platform
To Help The Engineer Achieve More

How does it work?

The core technology of Neural Concept shape are 3D convolutional networks that learn to predict the output of physical simulations or experiments based on the input shape’s geometrical properties. They can be used as complements to the traditional numerical simulation and experimental methods so as to alleviate the need for actual simulations or experiments along the conception pipeline. This dramatically accelerates and reduces the cost of the design process.

This proprietary deep learning technology is also fully integrated with state-of-the-art shape optimisation algorithms. Therefore, when relevant, the conception process can even be completely automated so as to find the optimal design(s) given a number of predefined objectives.

Customers Stories

Neural Concept and Bosch: Successful Applications of 3D Deep Learning based Surrogate Models

NUMECA uses Neural Concept’s Deep Learning Platform to study the Nature of Turbulence

Miniswys uses Neural Concept Shape for the Design Optimization of Customized Ultrasonic Actuators


PSA Groupe and Neural Concept Collaborating on External Aerodynamics

Airbus and Neural Concept Collaborating to further Accelerate their Engineering Processes

Preliminary Designs - Fixed Wing UAV

SenseFly, AirShaper and Neural Concept, Designing the Ultimate Drone

Case Studies

Satellites: A Smarter Design regarding the Thermal Constraints

Formula 1: Multiple Connected Components and Long-range Aerodynamic Correlations

Volumetric Field Predictions: A Benchmark using Neural Concept Shape

Speed Bicycle: Our Optimized Aero-bike broke Two World Records!


EPFL Innovation Park, Batiment C, 1015 Lausanne


Landsberger Straße 155,
80687 München

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