Built-In Interpretability Layers: Genesys embeds algorithmic transparency tools – CAMs (Class Activation Maps), UMAPs, and edge detection – directly into its architecture. These expose how predictions are made at each layer, enabling atomic-level confidence scoring.

Architectural Efficiency (MUM + SOM): Our Multi-Unimodal framework and proprietary training techniques enable adaptive multimodal learning with less training data, lower compute costs, and better out-of-sample distribution performance.

Physics-Informed Design: Integrates structural constraints and conformational dynamics and thermodynamic endpoint approximations.