Why finding where a product is made is an AI problem

A barcode tells you where a product was registered. Not where it was made. Pick up any product at the grocery store. Flip it over. See that barcode? The first three digits tell you which country it was registered in. Starts with 300-379? France. 400-440? Germany. 890? India. Most people (including me, before I started working on this) assume that's where the product is manufactured. It's not. Not even close. A French brand can register barcodes in France and make everything in China. A German company can produce in Poland. That 3-digit GS1 prefix matches the actual manufacturing country about 40% of the time. Basically a coin flip. I'm building Mio , an app that lets you scan a barcode and find where a product is actually made. What I thought would be a fun database project turned into one of the most interesting AI engineering challenges I've worked on. Here's why. Fair warning: I'm a developer, not a data scientist. Some of what I'll share in this series (variance exists! you need mo