Question

A financial services firm wants to build a system that answers analyst questions like 'Summarize the risk factors from the three latest 10-K filings for Company X and compare them to sector peers.' The number of documents to retrieve and the comparison steps vary per query, and the system sometimes needs to call a live market-data API mid-workflow depending on what the question asks. The team must decide how to structure the application. Which design approach best fits these requirements?

Accepted Answer

An agent with access to a retrieval tool and a market-data API tool, allowing the LLM to reason about which tools to invoke and in what order per query

Answer

A fixed sequential chain with predefined steps: retrieve documents, summarize, then compare, using the same tool order for every query

Answer

A single large prompt that stuffs all possible 10-K filings and market data into the context window and asks the model to answer directly

Answer

A batch fine-tuning job that trains the base model on all historical 10-K filings so it can answer from parametric memory