Self-Healing Product Catalogs: Drift-Aware Computer Vision for Retail & CPG on Databricks

Product catalogs are living things — new packaging, regional variants, seasonal SKUs are always cycling through — and every change impacts the model's accuracy. Neurolabs runs image recognition across 20,000+ SKUs in 28 markets, generating millions of shelf crops every month. Most are routine; only a handful contain the signal that makes the next model better — a new pack variant, a misclassified flavour, a confused competitor. We've moved that selection loop onto Databricks. Inference results land in Delta, every crop is scored for training value, and Unity Catalog governs which crops feed the next model and surfaces catalog-health metrics back to the CPG brands that own the SKUs. The result: a product catalog that heals itself, and a computer vision model that gets sharper with every shelf photo.