Your question is Pretrained LLM vs Fine-Tuning. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the trade-offs between using a pre-trained LLM versus fine-tuning a model on proprietary data.
Give a practical recommendation framework covering data requirements, expected quality gains, inference latency, training and serving cost, privacy, maintenance, and hallucination risk. Describe how you would evaluate both approaches before selecting one, including safeguards against proprietary-data leakage and prompt injection.