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Vinasoy and Renova Cloud have developed an AI-based shelf-image scoring project on AWS to shorten data processing time, improve accuracy and transparency in evaluating in-store display activities, and enhance operational efficiency and sales optimization across their store network.
The solution can automatically recognize products, analyze shelf images, assess compliance with predefined criteria, and compute scores. It combines AI, machine learning, Generative AI, and cloud infrastructure to move from manual evaluation to automated scoring.
Previously, shelf display evaluation depended on staff photography followed by image uploads for manual assessment. As the number of stores increased, this approach required substantial resources and time, limiting speed and consistency.
By reducing reliance on manual processes, the project delivers faster, more accurate, and more consistent evaluations. The time from photo capture to results is significantly shortened, supporting a shift toward near real-time shelf governance.
Using the same evaluation standards across stores is intended to minimize subjective bias, improving fairness and transparency for stores, sales staff, and managers. It also helps standardize shelf imagery across the system.
The project is expected to improve product presence at stores and the customer shopping experience by making it easier for consumers to find products and spend less time choosing.
Vinasoy described digital transformation as an ongoing process of investing in technology, data, and automation to strengthen governance and operational efficiency. The AI shelf-evaluation initiative is positioned as part of building a data-driven governance model to support faster, better decisions.
In the near future, Vinasoy and Renova Cloud Vietnam plan to expand AI solutions, including Agentic AI for distribution, marketing, and customer service, as part of their broader digital transformation efforts.
— Ánh Dương, Thanh Niên Việt
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