Technical note presents a framework for auditable artificial intelligence systems in healthcare, emphasizing privacy and knowledge retrieval.
This whitepaper introduces the Dynamic Language Model (DLM), a structured software architecture for local, auditable, database-grounded artificial intelligence systems. The framework organizes interaction through defined logical layers, operational routing, verified knowledge retrieval, correction-based updates, persistent state management, and human review for ambiguous or out-of-schema queries. Unlike conventional black-box AI workflows that rely primarily on probabilistic generation, DLM separates calculation from verified knowledge storage and emphasizes auditability, privacy, and operational continuity in healthcare and other regulated environments.
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Capote Yunior (2026) studied this question.
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