AI-driven solution for analyzing and interpreting data from PDFs and other textual resources using RAG and Hybrid Retrieval Models

Analyzing and interpreting data from unstructured resources such as PDFs presents significant challenges. This paper introduces an AI-driven solution that uses a hybrid approach by combining vector embeddings and knowledge graphs with multi-document analysis and metadata extraction. This approach ensures contextually rich responses. The multi-document analysis feature enables comparative insights while the metadata extraction provides source traceability and proof of authenticity. This system gives fast responses with source annotation which makes it suitable for research, legal and enterprise applications.