This invention describes a system that creates specialized AI assistants, called digital subject matter experts (dSMEs), by capturing knowledge from human experts through conversations and then organizing it. When a user asks a question in natural language, a chatbot routes the request to the most relevant dSME by comparing the request to descriptions of the available dSMEs using vector similarity. The selected dSME then attempts to answer the question or guide the user, potentially using external tools if its own knowledge is insufficient.
Why it matters: The claims describe a system for routing natural language requests to domain-specific AI models using vector similarity. While this was technically feasible in 2024, rapid advancements in LLM reasoning, knowledge extraction, and agentic capabilities by 2026 make the system's core functions of capturing expert knowledge conversationally and providing nuanced guidance significantly more effective and automated.
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