Abstract: Employing artificial intelligence to inform nuclear fuel procurement decisions is discussed. One example method includes accessing a database that characterizes terms of a set of transactions in a set of time frames. The transactions are transactions to procure material such as nuclear fuel assemblies or a precursor material for nuclear fuel assemblies obtained from procurement stages of a set of nuclear fuel procurement stages. The method also includes determining for the time frames, based on the database, a first range of values indicating a total expected supply of the material and a second range of values indicating a total expected demand for the material. The method further includes selecting an action in connection with the material from a set of potential actions, based on an analysis of the database, the first range of values, and the second range of values and outputting an indication of the selected action.

Abstract: A system for prioritizing trim requests can include an image processor that identifies a location associated with a customer trim request that includes an image of vegetation and industrial equipment and marks the vegetation and the industrial equipment visible in the image associated with the customer trim request. The system can also include a vegetation maintenance analyzer that searches for a match between the identified location associated with the customer trim request with a location associated with one of a past executed service ticket and a pending service ticket. The maintenance analyzer generates a maintenance profile for the customer trim request based on the results of the search and data in the customer trim request. The system can further include a priority engine that assigns priority to the customer trim request based on the maintenance profile for the customer trim request.