You are defining an enterprise architecture where language models need to answer questions using internal knowledge instead of relying only on pretraining. The design needs to cover how retrieval, grounding, and model behavior fit into a production NLP stack.
How would you incorporate AI/ML fundamentals, such as LLMs and RAG, into an enterprise architecture?