Question

A financial services company wants to build a customer support assistant that can answer questions about a customer's account. A single request may require the assistant to: (1) look up the customer's current account balance from an internal transactional database, (2) retrieve relevant policy explanations from an internal knowledge base of PDFs, and (3) perform a currency conversion calculation before presenting the final answer. The team wants a design where the LLM dynamically decides which capability to invoke based on the user's question. Which application design best fits these requirements?

Accepted Answer

An agent that reasons over the request and selects among defined tools: a SQL/function-calling tool for the balance lookup, a vector-search retriever tool for policy documents, and a calculator/code tool for currency conversion

Answer

A single large prompt that concatenates the full account database, all policy PDFs, and conversion tables into the context window for every request

Answer

A pure RAG pipeline that embeds the user question, retrieves the top-k policy chunks, and passes them to the LLM to generate all answers including balances and conversions

Answer

A fine-tuned model trained on historical account balances and policy text so it can answer all three types of questions without any external calls