RetailSupply Chain

How Super-Pharm Uses Vertex AI to Improve Inventory Accuracy from 50% to 90%

Super-Pharm leveraged Google Vertex AI for ML-powered demand forecasting, improving inventory accuracy from 50% to 90% and making forecasting 10x more efficient.

Outcomes

50% to 90%Inventory Accuracy
10x improvementForecasting Efficiency

Tools & Technologies

1GG
Google Gemini
Google multimodal AI model family
2GB
Google BigQuery
Serverless enterprise data warehouse for analytics
3GV
Google Vertex AI
Google Cloud unified ML platform for building, deploying, and scaling AI models and generative AI applications.

AI Categories

Challenge

On-premise systems could not keep pace with data volumes for tens of thousands of products, causing stockouts, abandoned carts, and lost revenue.

Solution

Migrated to Google Cloud with Vertex AI for ML-powered demand forecasting, BigQuery for data analysis, and Gemini AI for automatic product categorization.

Full Story

Super-Pharm, a leading pharmacy and beauty retail chain, struggled to predict customer demand for tens of thousands of products. On-premise systems could not handle growing data volumes, resulting in abandoned carts, stockouts, and lost revenue.

Access 449+ AI use cases, 414+ tools, and adoption signal rankings.

Source

GOOGLE CLOUD
January 2025
Original case study

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