Your question is Embeddings and Vector Search. 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).
How would you use embeddings and vector search to power semantic retrieval for enterprise documents at Morgan Stanley?
Keep the answer focused on retrieval quality, latency, and safety. Assume the system must support permissioned internal documents, avoid hallucinated answers, and resist prompt injection from untrusted content.