Abstract: A system and method of curating machine learning training data for improving a predictive accuracy of a machine learning model includes sourcing training data samples based on seeding instructions; returning a corpus of unlabeled training data samples based on a search of data repositories; assigning a distinct classification labels to each of the training data samples of the corpus; computing efficacy metrics for an in-scope corpus of labeled training data samples derived from a subset of training data samples of the corpus that have been assigned one of the plurality of distinct classification labels, wherein the efficacy metrics identify whether the in-scope corpus of labeled training data samples is suitable for training a target machine learning model; and routing the in-scope corpus of labeled training data samples based on the efficacy metrics.