Case Study: eBay Motors achieves faster photo categorization and lower costs with Firebase

eBay Motors uses Firebase ML to quickly categorize images, reduce costs and improve user experience

eBay Motors needed a way to automatically categorize car photos uploaded through its mobile app, since manually tagging images as exterior, interior, or engine was slowing down listings and adding unnecessary effort and cost. The company turned to Firebase, specifically AutoML Vision Edge, to streamline the upload experience and reduce engineering and server overhead.

Using Firebase, eBay Motors moved from concept to prototype in just one week with its own data set, and only needed about 20 hours of data labeling to get the model ready for production. The solution improved listing creation speed, lowered costs, and enhanced the seller experience, with Firebase helping eBay Motors deliver a faster, more efficient app workflow.

eBay Motors

Jake Hall

Head of Native Apps