Tender Recommendation System is a Flask-Based AI-Powered Tender Search Platform Developed by AI

Tender Recommendation System is a Flask-Based AI-Powered Tender Search Platform Developed by AI

Mr. Salim Khan1 Rushikesh Kathe2, Prathmesh Joshi 3,Anushka Patil4

*1 Assistant Professor, Department of Information Technology, Matoshri College of Engineering & Research Centre, Eklahare, Maharashtra, India

*2,3,4 Students, Department of Information Technology, Matoshri College of Engineering & Research Centre, Eklahare, Maharashtra, India

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Abstract— This project presents Tender recommendation System, an AI-driven web application designed to streamline the process of discovering relevant tender opportunities through natural language search and adaptive feedback mechanisms. Built using a Flask-based backend, the system integrates OpenAI's language models for semantic query understanding and employs Elasticsearch for dense vector similarity matching. It supports advanced filtering by country and publication date while incorporating user feedback to iteratively refine the relevance of search results. The application ensures secure access through token-based authentication and features a responsive user interface for an enhanced user experience. By combining natural language processing, vector search, and feedback-driven learning, Tender On Time significantly improves the accuracy and efficiency of tender retrieval, offering a robust solution for both public and private sector procurement needs.