I Tested Jev for E-Commerce

In this video, I test Jev by TypeSafe AI to see where it actually fits into e-commerce - and whether it’s useful for real operational decision-making. Rather than using a traditional LLM to generate text, Jev is designed to make structured decisions from defined inputs and constraints. To put that to the test, I walk through an e-commerce warehouse selection use case where Jev needs to decide which fulfillment location should handle an order. We’ll look at criteria like inventory availability, customer distance, estimated delivery time, fulfillment cost and warehouse workload - then change the business priorities to see how Jev adapts its decision. I’ll also break down where this type of system makes sense compared with simply writing deterministic rules in code. For straightforward logic, adding AI can create unnecessary complexity. But once you have a large number of competing criteria, changing priorities and edge cases, tools like Jev start to become much more interesting. If you’re building custom e-commerce systems, fulfillment logic or other operational workflows, this video should give you a practical idea of where decision models like Jev could fit. 00:00 Intro & The Jev Hype 00:23 How Jev Makes Decisions 01:07 The E-Commerce Challenge 02:24 MedusaJS + Vercel AI SDK Setup 04:01 Testing Warehouse Selection 05:52 Changing the Fulfillment Priorities 06:39 When Does Jev Actually Make Sense? 07:12 Custom E-Commerce Development If you’re looking for a software development agency to help build or scale a custom e-commerce platform, get in touch with us at 306 Technologies: https://www.306technologies.com/ Connect with me on LinkedIn → www.linkedin.com/in/raj-mahil Follow me on Twitter/X → https://x.com/RajFrom306 #ecommerce #AI #medusajs #headlesscommerce