The performance of this methodology is demonstrated across diverse organic reactions, an S N 2 reaction between the fluoride ion and chloromethane in implicit water (R1), the methyl shift of 2,2-dimethylisoindene to 1,2-dimethylindene in the gas phase (R2) and glycosylation reaction between acid-activated α-trichloroacetate and i-PrOH in explicit DCM (R3). Overall, the WTMetaD/WTMetaD-IB AL provides an efficient approach to training MLPs for reactive processes without prior knowledge of TSs or recreation pathways. This allows for an in-depth study of the reaction dynamics and the influence of temperature and solvent on the mechanism. While WTMetaD-IB still requires some knowledge of the system to define CVs, we envision that the use of emerging automated methods to identify CVs from limited trajectory data will further improve its efficiency.