Retail teams relied on manual store visits and shelf inspections to identify products, count inventory, and detect out-of-stock items. This process was time-consuming, costly, and prone to inconsistencies and human error. Manual data capture and reporting also delayed access to accurate, store-level inventory insights, making it difficult to respond quickly to stock gaps and merchandising needs. The organization needed an automated, scalable solution to recognize products, capture shelf inventory, and accelerate retail audits using AI and Computer Vision.