SearchApi vs AnswerLine

Coverage

SearchApi's plans

As published on searchapi.io/pricing, checked 2026-09-17. 100 free requests on sign-up. Their pricing page says at most 20% of a plan's credits can be used in an hour.

Price per request

SearchApi figures are one search on the Developer plan and, in brackets, Octo 5M; its pricing page lists no per-engine differences. This API's dollar figure is its credits per request at the credit price of the lowest paid plan. Reference plan: Lite.

How requests, geo, billing and delivery work

Where SearchApi is stronger

• Bing, Amazon, YouTube, DuckDuckGo, Baidu, app stores, travel sites and ad libraries share the same key and price.
• One flat search price, down to $1 per 1,000 on its largest plan, applies to an AI answer and a Google page alike.
• An enterprise zero_retention option disables logging and storage per request.

Choose this API when the answer has to come from a specific market (every assistant here takes country and US state), when you need Grok, or when prompt sets run as async batches delivered to webhooks. The guide below compares the requests.

Which to pick

Pick SearchApi when you want one key and one flat per-search price across a very wide set of engines (Google verticals, Bing, Amazon, YouTube, app stores, ad libraries) and the AI answers you need are fine without market targeting, or when the enterprise zero-retention option is a requirement.

Pick this API when the AI answer must come from a specific market, because every assistant here takes country and a US state; when you need Grok; or when prompt sets run as async batches with idempotency keys and webhooks rather than a synchronous loop.

Why market targeting decides most evaluations

Assistants that search the web can answer differently by market: the providers, regulation and availability behind a question like “best bank for small business” are local. A visibility report that doesn’t pin the market can’t say which market it describes, and can’t be reproduced.

SearchApi’s docs for its ChatGPT, Perplexity, Gemini and Bing Copilot engines list the query, the API key and an enterprise retention flag, plus a few engine options (web search and entity expansion for ChatGPT, source connectors for Perplexity), and no location or country parameter (checked 2026-09-17, searchapi.io). Its Google engines are the opposite: location, uule, coordinates, gl and hl.

On this API, the assistants take:

• country: ISO 3166-1 alpha-2, required on ChatGPT and the other assistants.
• state: a US state, optional.

Google Search takes country, location (City,Region,Country), uule, hl and device.

If your reporting is single-market and the provider’s default market is yours, this matters less. If you sell reports per country or per state, test it first on the free credits.

Migration: the same ChatGPT request

On SearchApi

curl -G "https://www.searchapi.io/api/v1/search" \
  -H "Authorization: Bearer $SEARCHAPI_KEY" \
  --data-urlencode "engine=chatgpt" \
  --data-urlencode "q=best business bank account for freelancers" \
  --data-urlencode "web_search=true"

Its docs list markdown, text_blocks, reference_links, cards, web_results, search_queries, citations and response_metadata in the response.

On this API

curl -X POST https://api.answerline.dev/v1/monitor/chatgpt \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "best business bank account for freelancers",
    "country": "GB",
    "include": { "markdown": true }
  }'

Field mapping

Google and the AI Overview

On SearchApi, the Google engine includes ai_overview, but when Google loads it separately the response carries a page_token, and you call the google_ai_overview engine with it within a minute (checked 2026-09-17, searchapi.io). Your code therefore has two paths and a timing constraint.

On this API the overview is part of the one Google request:

import { Client } from "@answerline/sdk";

const client = new Client({ apiKey: process.env.API_KEY!, baseUrl: "https://api.answerline.dev" });

const { result } = await client.google({
  query: "business bank account freelancers",
  country: "GB",
  hl: "en",
  include: { aioverview: { markdown: true } },
});

if (result.aioverview) {
  for (const s of result.aioverview.sources) console.log(s.position, s.url);
}

result.aioverview is either the overview or null when Google showed none.

From a synchronous loop to async batches

SearchApi’s documented requests are synchronous, and its pricing page caps use at 20% of a plan’s credits per hour. A monthly plan used for a weekly prompt run needs that spread planned.

This API has no hourly credit cap; the limits are requests per second, concurrent running tasks per plan, and a queue for the rest (rate limits). A weekly run is a set of batch calls:

import os, requests

prompts = ["best business bank account for freelancers", "Monzo or Starling for sole traders?"]
tasks = [
    {
        "taskType": engine,
        "payload": {"prompt": p, "country": "GB"},
        "idempotencyKey": f"bank-{i}-{engine}-GB-2026-W38",
        "webhook": {"url": "https://your-app.com/hooks/answers"},
    }
    for i, p in enumerate(prompts)
    for engine in ("CHATGPT", "GEMINI", "COPILOT", "GROK")
]
r = requests.post(
    "https://api.answerline.dev/v1/async/task/batch",
    headers={"Authorization": f"Bearer {os.environ['API_KEY']}"},
    json=tasks,
    timeout=60,
)
for item in r.json()["results"]:
    if not item["success"]:
        print(tasks[item["index"]]["idempotencyKey"], item["error"]["code"])

Use the week in the idempotency key so a rerun of the same week is refused rather than duplicated, and next week’s run gets fresh keys.

Comparing cost

SearchApi charges one search per successful request whatever the engine, with the per-search price falling on larger plans. This API charges per engine in credits (5 for ChatGPT, Copilot and Grok tasks, 4 for Gemini, 3 for a one-page Google Search plus 2 for the AI Overview, and 2 more for synchronous calls); the credit’s dollar value depends on the plan on pricing.

1. Count successful answers per engine per month.
2. For SearchApi, count one search per answer, plus a second request for Google queries whose AI Overview needs a page token; measure that share on your queries.
3. For this API, sum credits per engine and pick the plan that covers them.
4. Check SearchApi’s hourly 20% cap against how bunched your runs are.
5. Price the engines both cover first, then add the rest separately.

Running both side by side before cutting over

Start with a parallel run: the same prompts, markets and schedule on SearchApi and on this API for one or two weeks, stored in the same table with a provider column.

1. Choose prompts for engines both sides cover (Copilot is SearchApi’s bing_copilot engine), and Google queries with AI Overviews.
2. Note that SearchApi’s assistant engines take no market parameter; run this API’s side in the market you believe SearchApi defaults to, and in the markets you report on.
3. Submit tasks here with webhooks, keyed by prompt, engine, market and day.
4. For Google, record on SearchApi whether a page_token follow-up was needed and whether it succeeded.

What to compare at the end of the run:

• Market sensitivity: how much answers here change between markets you report on. If they change a lot, an untargeted series isn’t comparable.
• Answer and citation overlap per prompt, against day-to-day variation on one provider.
• AI Overview capture including page-token follow-ups.
• Hourly-cap impact: runs delayed by SearchApi’s 20% hourly cap versus queue wait here.

Cut over one engine at a time and keep the parallel data: it is the only record of how the switch itself moved your numbers.

Handling errors after the switch

SearchApi bills only successful searches with a 200 status, per its pricing page, so a client written for it may retry other statuses freely; here, follow the retry rules below instead.

This API’s errors carry a stable code to branch on (authentication and errors):

Every response carries an X-Request-Id; send your own to tie a request to your logs, and quote it to support. The TypeScript SDK applies this retry policy for you.

Decision checklist

1. Per-market AI answers? Needs country/state on the assistants: this API.
2. Grok? This API.
3. Dozens of non-AI engines on one key? SearchApi.
4. Scheduled volume without your own queue? Async tasks and webhooks here.
5. Per-request zero retention? SearchApi documents it for enterprise requests.

Pitfalls

• Assuming a default market is yours. Record the market with every answer; if the provider doesn’t let you set it, record that too.
• Expired page tokens. On SearchApi, fetch the AI Overview immediately or you lose it for that search.
• Bursty schedules against an hourly cap. Spread runs, or use a provider with a queue.
• Comparing text_blocks to text. Structure differs; compare markdown to markdown when diffing answers across providers.

Start with the quickstart or the Copilot engine page.

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