AI MEETS INVENTORY: EMPOWERING STOCK MANAGEMENT WITH REAL-TIME ANALYSIS POWERED BY AI

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dc.contributor.authorGerrard Keneth Sahol
dc.date.accessioned2026-04-28T07:51:48Z
dc.date.issued2025
dc.descriptionEffective inventory management is vital for small to medium-sized businesses, yet many rely on manual or spreadsheet-based systems, leading to errors and inefficiencies. This project introduces an AI-Enhanced Inventory Management System that automates stock tracking and improves decision-making. The system integrates PHP, MySQL, JavaScript, and Tailwind CSS for development, with the OpenAI API powering an AI-driven chatbot for real time user interaction. Following an Agile methodology, the project emphasizes iterative development, ensuring the system adapts to user needs. Key functionalities include real-time stock updates, predictive analytics for stock trends, and role-based access control. The system is rigorously tested for performance, reliability, and usability to meet both functional and non functional requirements. Ultimately, the deployment of this system aims to enhance inventory accuracy, reduce margin of error, and provide businesses with actionable insights, contributing to more efficient and effective inventory management practices.
dc.identifier.urihttps://scholarhub.unimas.my/handle/123456789/549
dc.language.isoEnglish
dc.publisherUniversiti Malaysia Sarawak
dc.relation.ispartofseriesFaculty of Computer Science and Information Technology
dc.titleAI MEETS INVENTORY: EMPOWERING STOCK MANAGEMENT WITH REAL-TIME ANALYSIS POWERED BY AI
dc.typeFinal Year Project

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