The Automated Mass Spectral Deconvolution and Identification System (AMDIS) is freeware extensively applied in metabolomics. However, datasets processed by AMDIS require extensive data correction, filtering and reshaping to create reliable datasets for further downstream analysis. Performed manually, these processes are laborious and extremely time consuming. Furthermore, manual corrections increase the chance of human error and can introduce additional technical variability to the data. Thus, an automated pipeline for curating GC-MS data is urgently needed.