ADAGOS introduces NeurEco©, a new generation of neural networks

Beyond learning the data, NeurEco learns the underlying rules for a more intelligent learning

They differ from large conventional neural networks that learn by memorization

NeurEco perfectly meets the challenges of Industry 4.0
It is an essential brick for Digital Twins and creates AI algorithms embeddable on small devices

NeurEco provides robust responses even with small datasets
Big data is rarely a reality in the industry which makes conventional solutions ineffective

NeurEco reduces ressources needed to implement Artificial Intelligence
It is in line with the objective of developing sustainable digital technology, with low environmental impact

NeurEco opens new horizons in AI

Tackles the major challenges facing classical AI approaches:
- It works even with a small amount of data
- It gives an accurate prediction for continuous phenomena

AI solution aimed at Industry 4.0 and Digital Twin
- Early detection of drift between the digital and the real copies
- Early update of the digital twin in case of drift
- Evaluation and update processes can be embedded on small chips

Automatic neural network creation
- Requires no further development by user
- Frees up developer time to focus on core tasks

Takes charge of creating the optimal network
- The parsimonious network is native, it doesn't come from simplification
- Minimizes computational resources and energy consumption

NeurEco generates models that are more accurate and much smaller than those from the state of the art
Click here to see a comparison between NeurEco and TensorFlow

Our customers

Our partners

What our clients say

En rupture totale par rapport à l’état de l’art, la société ADAGOS arrive à créer des modèles réduits ayant un grand nombre de paramètres (plusieurs centaines dans les cas considérés). Cela veut dire que ces outils ne semblent pas être affectés par ce que l’on appelle la malédiction de la dimension (curse of dimensionality). Cela parait d’autant plus étonnant que nos paramètres varient dans des intervalles très larges et ont un caractère discret aussi bien qualitatif que quantitatif.

Jean-Marie Hamy Technical Project Manager and Design Authority @ Framatome

Les enjeux sont considérables pour les systèmes embarqués et les applications médicales. De ce fait, nous maintenons une veille technologique et nous sommes en contact avec les universités les plus prestigieuses pour scruter la moindre évolution dans le domaine. Mais, il n’était pas nécessaire d’aller chercher bien loin, l’innovation de rupture peut venir d’une petite startup toulousaine appelée ADAGOS.

Michel Rochette Director of research @ Ansys France