To highlight CARE capabilities, we have selected three applications of industrial relevance and increasing complexity. We start by benchmarking activity against an open experimental dataset. Obtaining systematic studies of experimentally measured reactivity is not straightforward but the CatTestHub database presents a good example, changing the metal on the same carrier and under the same conditions for methanol decomposition. The second example illustrates a chemical reaction network in electrochemical environments. Selectivity is key to processes and typically depends on a set of two competing steps with small energy differences, in the range of few meV, thus being challenging in terms of accuracy, even more for data-driven estimators. To check the validity of CARE in predicting selectivity patterns in electrochemical applications, we analyzed the steps towards C 3 products on Cu(100)