Stationery Inventory Management System(SIMS)

Stationery Inventory Management System(SIMS)

Dhiraj Kailas Ade
Dept. of Artificial  Intelligence
G.H. Raisoni College Of  Engineering
Nagpur,India
dhirajade754@gmail.com

Dr. Kotadi Chinnaiah
Dept. of Artificial  Intelligence
G.H. Raisoni College Of         Engineering
Nagpur,India
kotadi.chinnaiah@raisoni.net

Prof. Madhuri Sahu

 Dept. of Artificial Intelligence

G.H. Raisoni College Of Engineering

Nagpur,India

madhuri.sahu@raisoni.net

  Gunjan Dinesh Rakhunde
Dept. of Artificial  Intelligence
G.H. Raisoni College Of  Engineering
Nagpur,India
gunjan.071003@gmail.com

Garima Raju Somkuwar
Dept. of Artificial  Intelligence
G.H. Raisoni College Of  Engineering
Nagpur,India
garima12somkuwar@gmail.com

Abstract—Inventory management plays a crucial role in ensuring operational efficiency and profitability, particularly in retail domains dealing with small, fast-moving consumer products. Traditional inventory tracking and sales systems often suffer from manual errors, lack of real-time updates, and poor integration with financial reporting tools. To address these challenges, this research presents the development of a robust and intelligent Stationery Inventory Management System (SIMS), tailored for small-scale businesses with a focus on female-oriented products such as earrings, bindis, and body sprays.

The objective of SIMS is to provide a comprehensive and user-friendly platform that streamlines stock management, automates GST-compliant billing, and delivers actionable financial insights. The system leverages real-time inventory tracking, itemized sales processing, and profit/loss analysis to enhance business decision-making. Additionally, SIMS incorporates a secure, role-based user management system to maintain data integrity and ensure authorized access.

Key features such as automated low-stock alerts, advanced search and filter options, customizable tax configurations, and QR/barcode integration are implemented to minimize manual efforts and improve operational accuracy. By integrating alerts and notifications for critical events and offering detailed reporting capabilities, SIMS not only reduces the chances of transactional errors but also optimizes day-to-day workflows.

In addition to the core system, this paper proposes a Level 1 prototype of an AI-based chatbot interface to be displayed on a digital screen at the shop entrance. This intelligent assistant will enable customers to inquire about product availability before entering the store, enhancing user experience and reducing in-store congestion. While this AI component is currently in the research and design phase, its partial implementation is planned as an extension to the existing system, contributing to the growing integration of artificial intelligence in small business retail management.

The development and deployment of SIMS demonstrate a scalable solution that enhances inventory visibility, supports growth, and simplifies financial oversight—ultimately contributing to the overall efficiency and success of modern retail businesses.