Corporate Language Model (CLM): Transforming Tacit and Fragmented Enterprise Knowledge into a Sovereign, Auditable, and Executable Corporate Intelligence Layer
The failure of enterprise AI deployment stems from the lack of a structured framework for coding decisions and execution logic. This paper proposes the Corporate Language Model (CLM) framework, which transforms enterprise-structured, unstructured, multimodal, and tacit knowledge into an ontological foundation to support reasoning and controlled execution. The framework includes five capabilities and four architectural pillars: a neural symbolic grid that couples generative models and knowledge graphs; a skill graph for achieving compositional interpretability; a digital twin that models functional areas as reasoning agents; and a deep security layer that enforces sovereignty, traceability, and human oversight. CLM adopts the “code is specification” paradigm to connect implementation intentions with executable outputs, making it an example of such a foundation-centered architecture. The paper contributes by defining CLM as an independent research subject; introducing the skill graph to achieve compositional interpretability; proposing the “wise listener” effect, which is the value-added basis of tacit knowledge capabilities over time; and providing evidence from a JCI-certified tertiary hospital in Brazil, illustrating the implementation of LG…