Abstract: The rapid digitization of public sector operations has transformed government procurement processes, but it has also introduced challenges such as information overload, fragmented systems, and limited personalization. Traditional e-procurement platforms mainly function as information repositories and require manual effort for schedule planning, compliance verification, and bid preparation, thereby reducing operational efficiency [1]. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), have demonstrated strong capabilities in automating decision-support tasks and generating intelligent recommendations in real time [3].

This paper proposes an Integrated AI-Driven E-Procurement System for Government Tenders, a web-based platform designed to streamline the tendering lifecycle through automation and conversational intelligence. Developed using the Flask framework and integrated with the Open Router API (GPT-3.5-turbo), the system enables dynamic generation of customized tender schedules, document insights, compliance guidance, and portal recommendations. Unlike conventional portals that provide static listings, the proposed system incorporates a context-aware AI assistant capable of interpreting natural language queries and generating personalized bidding strategies.

The platform also includes secure user authentication with encrypted password storage using SQLite and automated email notifications upon login. Experimental validation indicates that the system reduces manual effort in procurement planning while improving transparency and decision-making quality. Future enhancements include integration with live government procurement APIs, multilingual support, and automated tender document parsing.

Keywords: E-Procurement, Government Tender, Artificial Intelligence, Large Language Model, Decision Support System, Chatbot, Flask, Open Router.

Downloads: | DOI: 10.17148/IARJSET.2026.13336