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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM46384

Tender recommendation System is a Flask-based AI-powered tender search platform developed by AI.

Stream/Area:

-

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Paper ID:

IJSREM46384

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MSKRK

Mr. Salim Khan1 Rushikesh Kathe2

PJ3

Prathmesh Joshi 3

AP

Anushka Patil4

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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.

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Cite This Article

Mr. Salim Khan1 Rushikesh Kathe2, Prathmesh Joshi 3, Anushka Patil4, "Tender recommendation System is a Flask-based AI-powered tender search platform developed by AI.," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 4, Apr 2025.

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Publication Date

10/5/2025

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Double-Blind Peer Review

Review Rounds: 2

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