AI RESEARCH
Expert Mind: A Retrieval-Augmented Architecture for Expert Knowledge Preservation in the Energy Sector
arXiv CS.AI
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ArXi:2603.14541v1 Announce Type: new The departure of subject-matter experts from industrial organizations results in the irreversible loss of tacit knowledge that is rarely captured through conventional documentation practices. This paper proposes Expert Mind, an experimental system that leverages Retrieval-Augmented Generation (RAG), large language models (LLMs), and multimodal capture techniques to preserve, structure, and make queryable the deep expertise of organizational knowledge holders.