Abstract: An auto-tagging engine receives a training set of data comprising documents including a set of tagged fields with each tagged field corresponding to a portion of the document. The auto-tagging engine trains a machine learned model using the training set of data. The trained machine learned model, when applied to a target document in a document management environment, identifies portions of the target document each corresponding to fields of the target document. For each field of the target document, the auto-tagging engine identifies text of the target document associated with the identified potions of the target document corresponding to fields. Natural language processing is performed on the identified text in order to identify field types for the fields. The target document is automatically modified to include a tag identifying the portion of the target document corresponding to each field and identifying a field type of the field.