Fusion Retrieval: Combining Vector Search and BM25 for Enhanced Document Retrieval

This AI-powered document retrieval system enhances search accuracy by combining FAISS (semantic search), BM25 (keyword-based ranking) and LLM-generated content. It improves legal research, academic studies, corporate knowledge management and AI-driven search engines.

• Can be implemented in legal firms for case law searches.

• Useful for academic research to find relevant papers.

• Helps corporations in retrieving internal policies and reports.

• Supports journalists in fact-checking and source verification.

• Assists medical professionals in retrieving patient case studies.

• Beneficial for HR departments to quickly access company policies.

• Used by law firms to analyze contracts and legal disputes.

• Helps PhD students and scholars in finding references for theses.

• Can be expanded for news agencies to search archives.

• Enhances financial research by retrieving market reports.