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dc.contributor.author | Muqadas, 01-134201-107 | |
dc.contributor.author | Shayan Abdur Rehman, 01-134201-081 | |
dc.date.accessioned | 2024-02-20T06:03:30Z | |
dc.date.available | 2024-02-20T06:03:30Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/123456789/16944 | |
dc.description | Supervised by Dr. Muhammad Asfand-e-Yar | en_US |
dc.description.abstract | The Inventory Management System is a comprehensive and feature-rich platform with a range of methodically built roles, including super-administrators, store admins, and salesmen. It serves the complex and changing needs of many stores. The foundation of a flawless, end-toend inventory management process, advanced sales analysis, and the use of cutting-edge AI and machine learning technologies for predictive stock ordering is provided by this multifunctional system. While store admins exercise fine-grained control over inventories and ensure that customers have a hassle-free shopping experience through sophisticated barcode scanning, super-admins manage the ecosystem as a whole and manage the onboarding of new stores. The system’s full toolkit includes the ability to add, edit, and remove products as well as provide thorough sales information for in-depth trend analysis and wise decision-making. It makes use of sophisticated algorithms to forecast the best stock replenishment times and amounts, and it recognizes underperforming items thanks to its exceptional surplus detection abilities. Overall, this platform improves operational effectiveness, lowers costs, and boosts customer satisfaction, making it a crucial resource for a wide spectrum of retailers looking to succeed in the cutthroat retail environment of today. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Computer Sciences | en_US |
dc.relation.ispartofseries | BS(CS);P-02088 | |
dc.subject | GoShoppin | en_US |
dc.title | GoShoppin | en_US |
dc.type | Project Reports | en_US |