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Web Search

AI search lets a project reach current information from the web, so answers reflect the latest data rather than only the model's training data and the documents you have indexed locally. Every answer that used search is annotated with the sites it drew from.

A conversation answering a product question, with a REFERENCES section below the answer listing the three source sites used

Getting Started​

There is nothing to set up and no API key to sign up for. Searches are proxied through Smartloop, so web search works as soon as you are signed in — on every device, with no per-machine configuration.

Combining your data​

Search is most useful alongside your own data rather than instead of it. Because a project already holds your documents, one prompt can draw on both — your documents for context, the web for what is current.

Product research is a good example. With your existing gear, specifications, or past purchases in the project, you can ask what to buy next: the assistant reads your documents to understand what you already own and what would fit, searches for current models, pricing, and reviews, and then recommends one — with the sites behind the recommendation listed underneath.

An answer whose REFERENCES block cites a local text file alongside two websites, showing a document and web sources used together

Annotated sources​

When an answer draws on search results, the sources used are listed in a REFERENCES block beneath it. Web sources link out to the original page, so you can confirm where a claim came from and read further. Documents from your own project appear in the same block, labelled by file type and openable directly — so it is clear at a glance which parts of an answer came from your files and which came from the web.

How it works​

  1. Your prompt is normalized into a search query — conversational filler such as "can you tell me" is stripped so the query matches the actual subject rather than the phrasing.
  2. The query goes to Smartloop's search endpoint, which returns result links.
  3. Up to ten candidate pages are fetched and converted to text (HTML and PDF are both handled).
  4. The candidates are re-ranked by relevance to your question, and the top three are kept as sources for the answer.

If search is unavailable for any reason — turned off for the project, this month's allowance used up, or no results — it is skipped silently and the model answers from what it already knows. You will see an answer without a REFERENCES block rather than an error.

Privacy​

Search is the one part of Smartloop that reaches off your machine, and only the query leaves it. You can turn off search from Project Settings.

Smartloop does not keep the query. Your account records only that a search ran — when, from which app, which backend answered, and how many results came back — so you can spot use you do not recognize in your own activity log. The wording, the results, and the pages behind them are never stored. The candidate pages are fetched and ranked on your device, so the sites you end up reading are not something we see either.

The only number we keep is the count itself, which is what the monthly allowance is measured against.

Multiple search providers power AI search. The two main providers we use are:

Checking your usage​

Web search is on by default. You can see whether it is active, how many searches you have used this month, and when the count resets at app.smartloop.ai/settings/websearch.

Within a project, the toggle under the prompt (⌘⌥S, or Ctrl+Alt+S) turns search on and off for that project.

Web search config

Summary​

AI search keeps a project current without giving up local execution: the model and your documents stay on your device, and only the search query leaves it. The annotated references make it clear which parts of an answer came from the web.