Retrosynthesis - the task of planning chemical reaction recipes to synthesize complex molecules - remains a bottleneck in the discovery of novel pharmaceuticals. We recently released RetroChimera - a model for predicting chemical reactions - which demonstrated robustness well outside of training distribution by transferring zero-shot to internal reaction data at a major pharmaceutical company. We also found that industrial organic chemists prefer predictions from RetroChimera over real patented reactions in terms of quality, revealing a high degree of alignment. In this demo, we will showcase the model, let attendees query it live, and show them how to interpret the results.