The first is ASKCOS which bases its predictions on graph neural networks 4 trained by Reaxys® data and has an impurity prediction module, 5 although underlying literature for the latter could not be found. The other is IBM RXN, 6 regarded as state-of-the-art, which uses transformer models based on NLP 7 and USPTO data. Both tools are widely used and perform well for main product prediction. Corresponding results are shown in Figure . In both cases, the amine main product was predicted, but the correct impurities were not recommended. ASKCOS does recommend a dimer but there are structural differences when compared to the correct 10 impurity. It is important to note that although both tools perform as intended, this highlights a potential for improvement when deviating from main product prediction. Furthermore, a more fine-grained understanding of the underlying data is needed when troubleshooting presented (or absent) predictions.