SpendIQ: AI Surplus Intelligence Platform
Author
Mr. VarunKumar, M.Sriram, V.Thivinprakash, S.Valluvan, S.Vignesh
Abstract
SpendIQ: AI Surplus Intelligence Platform is a software solution designed to efficiently analyze financial transactions, monitor spending patterns, and identify surplus funds using Artificial Intelligence (AI). The system automates key financial processes such as expense tracking, budget monitoring, and financial record maintenance, reducing manual effort and minimizing errors. It provides real-time insights into income and expenses, helping users avoid unnecessary spending and improve savings. The system includes features such as expense categorization, budget management, surplus prediction, and AI-powered financial reporting tools that support better decision-making. By maintaining accurate financial records, it improves financial efficiency and enhances resource utilization. Additionally, the system ensures data security and easy access through a user-friendly interface. Overall, the SpendIQ: AI Surplus Intelligence Platform helps users streamline financial management, reduce unnecessary expenses, and maximize surplus funds, making it an essential tool for smart financial planning.
Keywords
AI Surplus Intelligence, Surplus Intelligence Platform, Enterprise spend AI, Spend analytics software, Enterprise procurement AI, Surplus spend management
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References
1.Sharma, P., & Verma, R. (2021). Design and Development of a Farm-to-Consumer Supply Chain Management System. International Journal of Agricultural Informatics and Technology, 12(3), 45–53.
2.Patel, K., & Deshmukh, S. (2020). Leveraging E-Commerce Platforms for Direct Farmer-to-Consumer Marketing.
Journal of Rural Development and Agricultural Economics, 48(2), 89–98.
3.Banerjee, A., & Iyer, R. (2022). Smart Agriculture and Digital Marketplaces: Enhancing Farmer Profitability through Technology. International Journal of Emerging Technologies in Agriculture, 10(1), 101–112.
4.Mehta, V., & Singh, N. (2023). Integration of IoT and Data Analytics in Farm-to-Home Food Supply Systems.
Journal of Smart Farming and Sustainable Systems, 8(4), 65–74.
5.Reddy, T., & Kumar, P. (2021). A Study on Digital Transformation in the Agricultural Supply Chain: Connecting Farmers and Consumers. International Journal of Information Technology and Management Studies, 15(2), 120–134