Published on: April 2026
KALPAVRIKSHA: AI-POWERED PERSONALIZED GOVERNMENT & PRIVATE SCHEMES RECOMMENDER SYSTEM
Vasundhara Deshmukh Mukund Deshmukh Samruddhi Tathe Mr. Pratik Wankhade
M. Faizan I. Khandwani
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Abstract
This research proposes KALPAVRIKSHA, an artificial intelligence-based personalized recommendation system designed to assist citizens in discovering relevant government and private schemes according to their eligibility. The proposed system uses a Knowledge Graph Enhanced Graph Neural Network (KEGNN) model to analyze relationships between user profiles and scheme eligibility criteria. The system integrates multilingual support, an AI chatbot assistant, voice interaction, and automated document validation to simplify the process of identifying suitable schemes.The proposed platform aims to improve welfare scheme awareness, increase accessibility, and enhance the efficiency of digital governance systems by providing intelligent recommendations to users. By connecting citizens with appropriate welfare programs, the system can significantly improve the utilization of government initiatives.
How to Cite this Paper
Deshmukh, V., Deshmukh, M., Tathe, S. & Wankhade, P. (2026). KALPAVRIKSHA: AI-Powered Personalized Government & Private Schemes Recommender System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i3.260
Deshmukh, Vasundhara, et al.. "KALPAVRIKSHA: AI-Powered Personalized Government & Private Schemes Recommender System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i3.260.
Deshmukh, Vasundhara,Mukund Deshmukh,Samruddhi Tathe, and Pratik Wankhade. "KALPAVRIKSHA: AI-Powered Personalized Government & Private Schemes Recommender System." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i3.260.
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- •Published on: Apr 03 2026
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