AI case study

VinasoyRetail display monitoring

Manual scoring across 34 provinces consumed 2,000 hours per cycle—and still reached only 17% of outlets. AI covers 70%+ in days.

Published

Key results

Sales Report Prep Time
5 mins
Scoring Cycle Time
1-2 days
vs 20+ days
Monthly Coverage Increase
>70%

Result highlights

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Where AI sits in the process

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The story

Context

A Vietnamese soy milk producer managing product displays across a retail distribution network spanning 34 provinces and cities.

Challenge

Manual image scoring consumed nearly 2,000 man-hours per cycle, covered only 17% of retail outlets per month, and took over 20 days to complete,...

Solution
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Quotes

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The company

Soy milk and plant-based beverage manufacturer and distributor in Vietnam.

IndustryConsumer Products
LocationQuang Ngai, Vietnam
Employees1K-5K
Founded1997

The implementation partner

Renova Cloud Vietnam logo

Renova Cloud Vietnam

renovacloud.com
Role in this case study

Developed the GenAI solution on AWS platform with Vinasoy for display monitoring.

IndustryTechnology
LocationHo Chi Minh City, Vietnam
Employees51-250
Founded2018

The vendor

Amazon Web Services (AWS) logo

Amazon Web Services (AWS)

aws.amazon.com
ROLE IN THIS CASE STUDY

Provided the cloud platform including Amazon SageMaker and Amazon Bedrock for Vinasoy's GenAI solution.

IndustryTechnology
LocationSeattle, WA, USA
Employees100K+
Founded2006

Use case

Vinasoy's Retail display monitoring is part of this use case:

Computer Vision
38 case studies(+38% YoY)
Proven impact?
Average
3.6Typical

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