International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI Policy Intelligence System Using Retrieval Augmented Generation, Semantic Search and Knowledge Graphs

Author(s) Mr. Mohd Faeez Ahmed, Mr. Krish Bansal, Mr. Chitraksh Tuli
Country India
Abstract Government welfare schemes and public policies are introduced for the sole purpose of supporting citizens in areas such as healthcare, education, employment, agriculture, financial assistance and what not. However, many people are still not able to access a majority of suitable schemes because they have low awareness, or scattered information is available, or due to complex eligibility conditions. Also the existing systems mainly rely on keyword-based searches which is a bit primitive at these times of advancements, they often fail to provide personalized recommendations. This research presents an AI-Powered Government Policy Intelligence and Recommendation System that uses Retrieval Augmented Generation, semantic vector search, BM25 retrieval, and large language models to provide accurate and personalized policy recommendations. The system combines semantic understanding with keyword-based retrieval to improve policy discovery and relevance. We have developed a modern conversational interface using Streamlit, while ChromaDB and Sentence Transformers were used for vector storage and embedding generations. openAI language models were integrated into this platform to generate structured and user-friendly responses as per the need. The proposed system supports intelligent policy search, eligibility checking, personalized recommendations, analytics dashboards, policy similarity analysis all according to the user’s needs. The solution improves accessibility and usability of government schemes while reducing the effort required for citizens to identify relevant policies. This project solves a real world problem that has not been looked into before.
Keywords Retrieval Augmented Generation, Artificial Intelligence, Semantic Search, Government Policies, Recommendation System, ChromaDB, NLP, Knowledge Graph, BM25 Retrieval, Cosine Similarity
Field Engineering
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-05-23
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E-ISSN 2582-2160
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