The plethora of factors that impact logistical efficiency also impact end-product pricing. A change in one computational ingredient (e.g., increased fuel cost, security-related shipment delay) can have a profound impact on the overall shipping cost and, consequently, the product price. Price determination should be malleable and based on real-time cost data. When leveraging AI tools, it is possible to incorporate cost-sensitive components, often combined with external dimensional data (e.g., weather patterns and transport time), to accurately predict an optimized price.