Data governance ai for predictive data retrieval based on multiple triggers

Abstract

This disclosure relates to protecting data in a distributed network. Data may be maintained across multiple endpoint devices, where different logical or geographical branches of the network have different data classification ratings that indicate different capabilities and limitations on data transfer and storage. Computer processes provide data governance in the distributed network to manage and transfer data through the network efficiently, provide predictive processing, and prevent unauthorized access to the data through sanitization and manipulation of the data. Artificial intelligence models may be leveraged to monitor data flow in the network and autonomously modify the network or data to enable multiple restricted data sources to be used together in a common workflow efficiently and securely.