The retailer Magnit is currently piloting an AI-based system to monitor the quality of fruits and vegetables during the receiving process. Employees use tablets to photograph products, allowing the AI to pre-fill quality checklists for subsequent verification by specialists. The company is also exploring video analytics to ensure compliance with receiving protocols, such as scale preparation and inspection procedures.
The pilot project is being conducted at one of the company's distribution centers. This initiative builds upon the existing mobile receiving system already deployed across all of Magnit's distribution centers. The target accuracy for the AI recognition system is set at over 95%. Following the pilot, the company intends to develop a cross-platform quality management system.
The new AI tools are part of a broader strategy to establish a unified digital quality control ecosystem. This platform will integrate web, cloud, and mobile interfaces to centralize data, including receiving results, photo and video evidence, laboratory reports, and supplier audit findings. The system also tracks cold chain compliance and factors contributing to inventory write-offs.
Magnit aims to implement end-to-end traceability for produce, covering the entire journey from suppliers to store shelves. This digitalization effort is a core component of the company's five-year program focused on reducing inventory losses. According to Vladimir Gabaraev, Director of the Quality Department, the goal is to create a digital footprint for every batch to minimize human error.