Native Web Search

Native web search is a toggle on the AI Model step that lets the model query the live web as part of generating its response. It is a capability built into the model provider's API — not a connector, not an MCP tool, and not a separate credential. When the toggle is on, the model decides when to search, what to search for, and how to incorporate the results.

This is different from tool-based search integrations like Brave Search or Firecrawl, where you wire a tool step into your agent workflow and control when it runs. Native web search is fully model-driven.

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Quick reference

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What is native web search?

When Web Search is enabled, the model's host (Anthropic, OpenAI, or Google) performs a search on the model's behalf during inference. The search results are injected into the model's context before it generates a response, grounding the answer in current information.

From your agent's perspective, you enable a toggle. The model handles everything else — query construction, result retrieval, and synthesis. You do not need to write a prompt that asks the model to search; it will search when it judges that the question requires current information.

Depending on the provider, the model's response may include citations or source references inline.

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Supported models

The Web Search toggle appears only on models that support this capability. The full list of supported models is below.

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Enabling web search

1. Open your agent in Agent Studio
2. Select the AI Model step
3. Open the Model tab in the right-hand panel
4. Scroll below Temperature to find the Web Search toggle
5. Toggle it on

The toggle is per-step. If your agent has multiple AI Model steps, enable it individually on each step that should use web search.

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When to enable / disable

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What the model searches — and what it receives

The model determines on its own when a search is needed and what query to issue. You do not write the search query and it is not visible to you in execution logs. The provider's infrastructure runs the search, retrieves results, and injects them into the model's context before it generates a response.

What this means in practice:

• You do not control the query. The model infers it from your prompt and the user's message.
• Results are not exposed as a step output. You cannot pipe them into other steps or inspect them directly. Use the Debug tab to review the model's full context if you need to understand what it retrieved.
• Citations may appear inline. Depending on the provider, the model may include source URLs or reference markers in its response. This is provider-specific behaviour and cannot be configured from Airia.

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Considerations

Latency

Each web search adds a round-trip to the provider's search infrastructure before the model generates text. Expect approximately 1–3 seconds of additional latency per execution. For real-time conversational agents this is usually acceptable; for high-volume batch pipelines it may not be.

Token usage

Search results are injected into the model's context window and count toward your token consumption. Responses from a web-search-enabled model typically cost more tokens than the same prompt without search. Monitor token usage in the Feeds view if cost is a concern.

Privacy

Determinism

Web search results vary by time, query phrasing, and provider index freshness. Two identical prompts sent minutes apart may produce different answers. If reproducible outputs are required — for automated testing, audit trails, or compliance workflows — keep Web Search off.

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Native web search vs. search tool integrations

Use native web search when you want live information without any plumbing. Use a tool integration when you need to inspect the results, pass them to other steps, or control exactly when the search runs.

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Troubleshooting