Effectively implementing artificial intelligence algorithms on embedded systems is a real challenge. Our parsimonious AI breaks down all barriers related to: Bulk constraint, Energy consumption, Computational resources, Data transmission bandwidth while meeting your requirements of accuracy, robustness and reliability.


A digital twin is a virtual representation of an object, process or system that spans its lifecycle, is updated from real-time data, and uses simulation and machine learning to help decision-making. Our parsimonious neural network technology is an asset for digital twin applications: Accuracy (which is a direct consequence of parsimony) allows the early detection […]


Our goal is to speed up design processes and to reduce time to market: NeurEco creates Reduced Order Models (ROMs) from a small amount of simulation data It goes beyond ROMs by creating a real-time copy of a complex high-fidelity simulation tool, from a few simulation results Beyond learning the data, NeurEco learns the underlying […]


Parsimony allows us to reduce the amount of data needed for learning. AI can then be deployed quickly Instead of collecting data for years, a week might be enough. Instead of collecting data for weeks, an hour might be enough… This asset is of capital importance in a constantly changing world. Indeed, the data collected […]