Forecasting Retail Inventory and Supply Chain Demand Using Claude Powered Generative AI and Spring Boot APIs

Naveen Kumar Vayyasi

Forecasting Retail Inventory and Supply Chain Demand Using Claude Powered Generative AI and Spring Boot APIs

Authors

Naveen Kumar Vayyasi

Keywords:

demand forecasting, generative AI, Claude AI, Spring Boot, retail inventory, supply chain management, microservices architecture

Abstract

The retail sector keeps on facing difficulties with inventory control and demand estimation thatlead to financial losses through the simultaneous sale of non-existent stock and the holding of too much stock.

References

Anderson, R. and Martinez, L. (2022) 'Large language models for business analytics: Capabilities and limitations', Journal of Business Intelligence, 15(2), pp. 178-195.

Davidson, M. and Kumar, P. (2021) 'Traditional statistical methods in retail forecasting: A contemporary review', International Journal of Retail Management, 48(3), pp. 312 329.

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Published

2022-08-10

How to Cite

Naveen Kumar Vayyasi. (2022). Forecasting Retail Inventory and Supply Chain Demand Using Claude Powered Generative AI and Spring Boot APIs . Journal of Computational Analysis and Applications (JoCAAA), 30(2), 970–982. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4887