In conclusion, we have developed an automated workflow for the identification and quantification of novel chemical compounds in a reaction mixture. We demonstrate that this approach can be used to deconvolute and analyze experimentally obtained, crude NMR spectra that contain multiple isomeric products. We present this workflow as a series of modules, so that practitioners can adapt it further to their needs. The method can enable researchers to automate analysis of high-throughput experimentation campaigns that generate large numbers of previously undescribed compounds. This contribution may transform our ability to generate training data for machine learning models and assist drug discovery campaigns during diversity-oriented synthesis.