Fusion Retrieval: Combining Vector Search and BM25 for Enhanced Document Retrieval
AI-driven document retrieval system using FAISS, BM25 and LLMs for fast, accurate search in legal, academic, corporate and research applications with citations.
$20 USD
$10.00 USD
Project Outcomes
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.
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Can be implemented in legal firms for case law searches.
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Useful for academic research to find relevant papers.
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Helps corporations in retrieving internal policies and reports.
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Supports journalists in fact-checking and source verification.
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Assists medical professionals in retrieving patient case studies.
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Beneficial for HR departments to quickly access company policies.
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Used by law firms to analyze contracts and legal disputes.
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Helps PhD students and scholars in finding references for theses.
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Can be expanded for news agencies to search archives.
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Enhances financial research by retrieving market reports.
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