fan-out search

Fan-out search is a search method that breaks a single question into several smaller questions, looks them up at the same time, and then gathers the results into one combined answer.

Think of it like this: instead of asking a librarian all at once, "Tell me about local restaurants, today's weather, and this weekend's events," you ask several librarians at the same time — "Where are good restaurants?", "How's the weather?", "What events are happening?" — and then someone pulls all their answers together into a single reply. The name comes from the way the question spreads outward into multiple branches, like a fan opening up.

A question people ask is often packed with several pieces of information in one sentence, and running a single search can easily miss parts of it. By splitting the question into different angles and searching each one separately, you can produce a broader and more accurate answer — which is why many AI search services now use this approach to improve answer quality.

Try asking an AI search tool a question that packs multiple pieces of information into one sentence. For example, ask something like "Tell me about restaurants in this area, today's weather, and events happening this week all at once." If the answer comes back neatly organized by category, there's a good chance that behind the scenes, your question was split into multiple sub-searches.