Google AI Overview

Google AI Overview is the AI-generated summary Google renders at the top of a Search results page. The API captures that block from a real browser — the live Google Search experience — and returns it as the same Envelope every other surface produces.


`surfaces` value	`google_ai_overview`
Alias path	`POST /v1/search/google_ai_overview`
Credits per capture	5 (charged only on success)
Provider	Google

What it returns

The AI Overview capture normalizes into the same canonical Envelope:

answer.text / answer.markdown — the Overview summary. markdown is always populated.
answer.blocks[] — structured blocks, each typed with text and referenceIds.
provenance.model — the observed model label and confidence.
provenance.surfacePresent — whether the Overview returned an answer.
provenance.region — requested vs. effective region.
evidence.sources[] — the cited/retrieved sources answer.blocks[].referenceIds point to. This is an own-fleet surface, so evidence.fanOut is { "provenance": "none", "queries": [] }.

Every surface normalizes to the same Envelope. Whether you capture Google AI Overview, ChatGPT, or Perplexity, you parse one shape, so the code below works unchanged across surfaces. See Output formats.

Request

Add google_ai_overview to surfaces on a standard POST /v1/search. A single-surface request with no webhook runs synchronously by default (a 200 with the Envelope inline); add ?mode=async for the durable fan-out path — one child per surface × region, returning 202 with a parent job.

curl -X POST "https://api.aisearchapi.dev/v1/search?mode=async" \
  -H "Authorization: Bearer $AISEARCH_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "best running shoes for flat feet",
    "surfaces": ["google_ai_overview"],
    "regions": [{ "country": "US" }]
  }'

const res = await fetch('https://api.aisearchapi.dev/v1/search?mode=async', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.AISEARCH_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    query: 'best running shoes for flat feet',
    surfaces: ['google_ai_overview'],
    regions: [{ country: 'US' }],
  }),
});

const job = await res.json();
console.log(res.status, job); // 202

import os
import requests

res = requests.post(
    "https://api.aisearchapi.dev/v1/search",
    params={"mode": "async"},
    headers={
        "Authorization": f"Bearer {os.environ['AISEARCH_API_KEY']}",
        "Content-Type": "application/json",
    },
    json={
        "query": "best running shoes for flat feet",
        "surfaces": ["google_ai_overview"],
        "regions": [{"country": "US"}],
    },
)

print(res.status_code, res.json())  # 202

The 202 carries the parent job and one dotted child id — read it with GET /v1/jobs/:id or receive it on a webhook.

{
  "jobId": "job_8t2q",
  "status": "processing",
  "children": ["job_8t2q.google_ai_overview.us"]
}

Per-surface alias

POST /v1/search/google_ai_overview targets this one surface — sync by default like any single-surface call. It holds the connection open and returns the result inline with 200 (the Envelope in children[0]), no polling. It accepts two convenience fields: prompt (alias of query) and country (flat sugar for regions: [{ "country": "..." }]).

curl -X POST https://api.aisearchapi.dev/v1/search/google_ai_overview \
  -H "Authorization: Bearer $AISEARCH_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "best running shoes for flat feet",
    "country": "US"
  }'

const res = await fetch(
  'https://api.aisearchapi.dev/v1/search/google_ai_overview',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AISEARCH_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      prompt: 'best running shoes for flat feet',
      country: 'US',
    }),
  },
);

const result = await res.json();
console.log(res.status, result.children[0].answer.markdown); // 200

import os
import requests

res = requests.post(
    "https://api.aisearchapi.dev/v1/search/google_ai_overview",
    headers={
        "Authorization": f"Bearer {os.environ['AISEARCH_API_KEY']}",
        "Content-Type": "application/json",
    },
    json={"prompt": "best running shoes for flat feet", "country": "US"},
)

print(res.status_code, res.json()["children"][0]["answer"]["markdown"])  # 200

Envelope

A trimmed capture, the same four sections (job, provenance, answer, evidence) you get from every surface.

{
  "job": {
    "id": "job_8t2q.google_ai_overview.us",
    "query": "best running shoes for flat feet",
    "surface": "google_ai_overview",
    "region": "us",
    "status": "completed",
    "warnings": [],
    "requestedAt": "2026-06-30T17:02:11.000Z",
    "completedAt": "2026-06-30T17:02:26.000Z"
  },
  "provenance": {
    "model": {
      "providerId": null,
      "observedLabel": "AI Overview",
      "inferred": true,
      "confidence": 0.6
    },
    "webSearch": { "enabled": true, "known": true },
    "triggerState": "search",
    "persona": "anonymous_default_model",
    "loginState": "logged_out",
    "surfacePresent": true,
    "region": { "requested": "US", "effective": "US" },
    "capturedAt": "2026-06-30T17:02:26.000Z",
    "callUuid": "call_9d8c7b6a5f4e3d2c1b0a9f8e7d6c5b4a",
    "schemaVersion": "2026-06-27"
  },
  "answer": {
    "text": "For flat feet, look for stability shoes with firm midsole support like the Brooks Adrenaline GTS and ASICS Gel-Kayano...",
    "markdown": "For flat feet, look for **stability shoes** with firm midsole support like the **Brooks Adrenaline GTS** and **ASICS Gel-Kayano**...",
    "blocks": [
      {
        "type": "paragraph",
        "text": "For flat feet, look for stability shoes...",
        "referenceIds": [0, 1]
      }
    ]
  },
  "evidence": {
    "sources": [
      {
        "id": 0,
        "url": "https://www.brooksrunning.com",
        "title": "Brooks Adrenaline GTS",
        "role": "cited",
        "cited": true,
        "charRanges": [[70, 91]]
      },
      {
        "id": 1,
        "url": "https://www.asics.com",
        "title": "ASICS Gel-Kayano",
        "role": "cited",
        "cited": true,
        "charRanges": [[96, 112]]
      }
    ],
    "fanOut": { "provenance": "none", "queries": [] },
    "mentions": null,
    "shopping": null,
    "ads": null
  }
}

If Google shows no Overview for the query, the child still completes: provenance.surfacePresent is false, job.warnings carries a surface_absent warning, and answer is empty. An empty capture costs no credits.

answer.markdown is always populated, and answer.blocks[] carry the answer as typed blocks. See Output formats for turning this into rendered text or structured data.

All surfaces

The full enum and how fan-out works.

The Envelope

Every field in the canonical per-surface result.

Endpoints

Account & discovery

Watches

By surface

What it returns

Request

Per-surface alias

Envelope

All surfaces

The Envelope

​What it returns

​Request

​Per-surface alias

​Envelope

All surfaces

The Envelope

What it returns

Request

Per-surface alias

Envelope