International Journal of Scientific Research and Engineering Development

Access to government schemes and welfare benefits remains complex for many citizens due to fragmented data and lack of awareness. The proposed AI-Based Government Schemes Recommendation System (AIGSRS) leverages Natural Language Processing (NLP), Machine Learning (ML), and Citizen Profiling to intelligently match users with suitable welfare schemes based on parameters such as age, gender, income, occupation, location, and interests. The system accepts user queries in natural language—either typed or spoken—and generates a ranked list of relevant schemes along with details on eligibility, benefits, and official application links. Its architecture integrates five core modules: User Profile Analyzer, Eligibility Predictor, Scheme Knowledge Base, Recommendation Engine, and Feedback Learning Module. Tested on 1000 citizen records, the AI-GSRS achieved an impressive 92% accuracy in matching correct schemes while reducing manual search time by 70%, thereby promoting inclusive and efficient access to government assistance through intelligent automation.