Case Study: a global retail brand achieves real-time inventory visibility and fewer stock errors with Intuz’s Databricks computer vision solution

Global Retail Brand cuts inventory errors by 85% with Intuz

Intuz developed a solution for a global retail brand facing challenges with manual inventory management. The customer struggled with empty shelves, high operational costs due to labor-intensive processes, and a lack of real-time stock visibility, all of which negatively impacted the customer experience.

The vendor built a computer vision solution on the Databricks platform, utilizing in-store cameras, CNN-based models, and automated data pipelines. This system provided real-time shelf monitoring and integrated insights directly into business systems. Intuz's solution led to an 85% reduction in inventory errors and cut labor costs by 40% through automation.