R&D institute


Philippe De Souza

+33 1 53 65 14 14



ESI was created in France in 1973 by Alain de Rouvray, current Chairman and President, with three other Berkeley Ph.D.s colleagues and partners (Jacques Dubois, Iraj Farhooman, Eberhard Haug). The company initially operated as a consulting company for European defense, aerospace and nuclear industries. ESI gradually developed sophisticated simulation techniques based on finite element analysis, and acquired a broad understanding of industrial processes and needs.

ESI is a world leading software editor for the numerical simulation of prototype and manufacturing process engineering in applied mechanics. The key to ESI's success is the use of realistic material physics, providing "as good as real" virtual solutions, in order to replace the lengthy trial and error processes on real prototypes. ESI has developed an extensive suite of coherent, industry-oriented applicationsto realistically simulate a product’s behavior during testing and real life use; to refine manufacturing processes for desired product performance, and to evaluate the effect of the environment in which the product is deployed.

ESI’s products represent a unique collaborative and open environment for End-to-End Virtual Prototyping, thus eliminating the need for physical prototypes during product development. This solution allows a productivity gain, innovation acceleration and significantly reduced costs.

Participation in EU Projects and International Activities

AWARE2ALL: CAE Simulation of crash/pre-crash integrated safety scenarios vehicle occupants with human body modelling HIPERMAT: Design of new metal alloys, and their manufacturing process, hydrosolidification LEVEL-UP: Simulation of fatigue of the manufacturing toolset in a hybrid twin approach, applied to predictive maintenance OSCCAR: Human body modelling for occupant safety in autonomous vehicles SUaaVE: Immersive driving simulation for Human-Centric development UPSCALE: Crash performance simulation of electric vehicles’ batteries, using model order reduction and multiscale simulation