온톨로지는 진정한 가드레일입니다: AI 에이전트가 비즈니스를 오해하는 것을 막는 방법

Enterprises are investing billions of dollars in AI agents and infrastructure to transform business processes. However, we are seeing limited success in real-world applications, often due to the inability of agents to truly understand business data, policies and processes. While we manage the integrations well with technologies like API management, model context protocol (MCP) and others, having agents truly understand the “meaning” of data in the context of a given businesis a different story. Enterprise data is mostly siloed into disparate systems in structured and unstructured forms and needs to be analyzed with a domain-specific business lens.sAs an example, the term “customer” may refer to a different group of people in a Sales CRM system, compared to a finance system which may use this tag for paying clients. One department might define “product” as a SKU; another may represent as a "product" family; a third as a marketing bundle. Data about “product sales” thus varies