Abstract: Systems, devices, and/or methods may implement one or more machine learning models for finding specific data/items from one or more enterprise resource platforms. The one or more machine learning models may be running on any new (e.g., fresh) transactions that may be fed to/from the one or more enterprise payment systems. The one or more machine learning models may be configured to determine an association between software (e.g., application, program, code, etc.) subscription, purchase, and/or a license and at least one transaction. The one or more models may learn the association and/or may adjust one or more future matches, for example based on the learned associations. Perhaps as the one or more models run, at least one confidence score may be associated with one or more, or each, match made. The confidence score may indicate the confidence and/or reliability of the one or more associations to an end user.