The use of computer-aided synthesis planning (CASP) started several decades ago but has gained a renewed interest recently with recent advances in machine. CASP is beneficial for both medicinal and process chemists as the tools provide suggestions on how to synthesize novel compounds and guide the optimization of reaction conditions. Coupling powerful machine learning models to large databases of reactions such as Reaxys, CAS, 5 Pistachio 6 or internal corporate Electronic Laboratory Notebooks (ELNs), have the potential to transform the way chemists approach synthesis.