Founded in 2009, the Israeli company uses a structure-based approach, where their model is trained on millions of Antibody-Antigen pairs in order to identify a template antibody against the desired target from existing human antibodies. It then uses a different ML model to predict mutations and guide evolution of the identified template to improve affinity and other biophysical properties.