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Multi-Source Search

How AI Search aggregates Wikipedia, news, finance, Brave, Diffbot and Exa into one progressive, streamed answer.

How aggregation works

When you run a query, AI Search fans it out to multiple sources in parallel rather than relying on a single index. Results are deduplicated, ranked and handed to the answer model with citations, so the response you read is grounded in what the sources actually returned.

SourceBest forTypical content
WikipediaBackground and definitionsEncyclopedic summaries and entity facts
News APIsCurrent eventsRecent articles and headlines
Finance APIs (Alpha Vantage)MarketsStock prices and financial data
Brave SearchGeneral web coverageWeb pages and fresh results
DiffbotStructured extractionClean article and entity data from web pages
ExaSemantic web searchConceptually relevant pages, not just keyword matches

Progressive answers

You never wait for the slowest source. AI Search returns a fast initial answer from the quickest sources, then enhances it as deeper results arrive — additional citations, refined figures and expanded context appear in place without re-running the query.

  1. 1

    Initial answer

    A fast first response streams in token by token, built from the sources that respond first.

  2. 2

    Enhanced results

    Slower, deeper sources finish and the answer is upgraded with more detail and citations.

  3. 3

    Follow up

    Ask a refinement in the same session — context is retained, so you do not repeat yourself.

Streaming responses

Answers are generated by leading LLMs and streamed as they are produced, so you start reading immediately instead of staring at a spinner. If the early part of the answer already covers what you need, you can stop generation and move on.

Rate limits by plan

Search throughput is tiered by subscription. Free covers casual use; Basic, Pro and Enterprise raise the ceiling for heavier research workloads. When you hit a limit, AI Search tells you exactly when the window resets.