System and method for processing shipment requests using a multi-service shipping platform

A method comprising:

• with a multi-tenant, multi-carrier shipping services platform:
• accessing multi-service tracking data for delivered shipments from shipping carrier computing systems of a plurality of shipping carriers, wherein the multi-service tracking data includes tracking data for a plurality of shipping carrier services for the plurality of shipping carriers;
• training a predictive machine learning model, based on the multi-service tracking data, to predict a time-in-transit for each of a set of package percentiles;
• receiving, from a client computing system, a shipment request for a new shipment via a public REST (Representational State Transfer) Application Programming Interface (API) of the shipping services platform, wherein the shipment request comprises a set of time-in-transit requirements, comprising a target time-in-transit for a target package percentile;
• generating a response to the shipment request using the set of time-in-transit requirements and the trained predictive machine learning model, wherein the response identifies at least one shipping carrier service that can be used for delivering a parcel within the target time-in-transit for at least the percentile of packages;
• and
• providing the response to the client computing system.