Abstract: Exemplary implementations may: receive, by a sales support microservice in communication with a trained model running on a server, a plurality of attributes; and feed the plurality of attributes to the trained model.

Abstract: Directed to methods and systems for automated fee generation through the use of machine learning for telecommunications projects. Exemplary implementations may: receive, by a sales support microservice in communication with a trained model running on a server, a plurality of attributes; and feed the plurality of attributes to the trained model. The trained model can retrieve historical data regarding fee prices, identify similar historical projects based on final fee prices and historical attributes of the respective projects, and refine a correlation between historical attributes and fee prices, which can be used in the generation of a fee price to provision a telecommunications project as a result of those attributes.

Abstract: The present disclosure describes systems, methods, and non-transitory computer readable media for determining project lifecycles and tracking opportunities in the telecommunications sphere. These systems, methods, and non-transitory computer readable media can access information for a project offering, receive input to modify the project offering's information, update the project offering information, generate deadlines or reminders for the project offering, and generate a display of the project offering's lifecycle track.