If a company has a 1,000-page internal wiki that updates daily, would you recommend RAG or fine-tuning? Why?

Why might you use a "Cross-Encoder" re-ranker after your initial vector retrieval? What is the trade-off in terms of latency?

If the retriever returns zero relevant documents, how do you prevent the LLM from making up an answer?

How would you adjust your pipeline if the source documents contained both text and complex financial charts/tables?