Various embodiments herein include an engine that uses data science, history, and trends to successfully determine and suggest the complimentary add on and upsell items that are tailored to at least some of the customer, current trends, product popularity, recommendations, and other such factors. One embodiment, in the form of a method, includes receiving, from a process involved in processing an open transaction, data representative of at least one of products and services that are subjects of the open transaction. The method further includes querying a recommendation engine for at least one of product and service recommendations based on the received data representative of products and services and receiving, in response to the query, at least one product or service recommendation. The method may then provide the at least one product recommendation to the process involved in processing the open transaction.