Data provenance is the documentation of where training data came from, how it was collected or structured, and what metadata supports review. In AI, provenance helps teams evaluate dataset quality, licensing, compliance, and suitability for a model’s intended use.
Provenance makes AI data inspectable. It helps legal, security, compliance, and model teams understand whether data is appropriate for training or evaluation.
Useful provenance signals vary by modality, but the principle is the same: buyers should be able to inspect what the dataset represents.