About
This Product Service Code (PSC) prediction service was developed by researchers at the Naval Postgraduate School and the Air Force Installation Contracting Agency. It is intended to improve personnel efficiency and consistency in selecting Product Service Codes.

Currently, humans classify product and service requirements into one of several thousand possible Product Service Codes. This is a tedious, time-consuming process that, for many areas of spend, tends to lead to inconsistent classification. This site provides machine classification of Federal acquisition requirements (i.e., a machine learning implementation) for this purpose.
Disclaimers
The appearance of hyperlinks on this site does not constitute endorsement by the Naval Postgraduate School, the Air Force Installation Contracting Agency or the U.S. Department of Defense. Further, mention of any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government. Any views and opinions expressed herein are those of the authors; they do not state or reflect those of the United States Government and shall not be used for advertising or product endorsement purposes.
Privacy Notice
This site only collects information on its visitors as is needed to provide the information, services, and/or assistance that are requested. Collected information includes information on vistors sent to the site by web browsers, such as internet protocol addresses, the date and time that site resources are requested, the content of queries, browser type and referrer information. Collected information is used in aggregate to help maintain and improve the site (e.g., to determine the number of visitors to different sections of the site, to ensure the site is working properly, to make the site more accessible and more useful to vistors). You may opt out of information collection by not using the site.
Copyright
Copyright and related rights in this work are waived through the CC0 1.0 Universal Public Doman Dedication. This work is in the public domain in the United States.