Initial work on ePADD began in 2010 based on the dissertation work of Sudheendra Hangal, then a Ph.D. candidate in the Computer Science department at Stanford. The ePADD project received funding from the National Historical Publications & Records Commission from 2012-2015 to develop the first full version of the software package. From 2015-2018, the project received funding from the Institute of Museum and Library Services to develop a further six versions of ePADD.
Over the past five years, ePADD has pioneered the application of machine learning and natural language processing to confront challenges that collection donors, archivists, and researchers routinely face in donating, administering, preserving, or accessing email collections. This includes screening email for confidential, restricted, or legally-protected information, preparing email for preservation, and making the resulting files (which incorporates preservation actions taken by the repository) discoverable and accessible to researchers.