Oxylabs vs AnswerLine

Coverage

Oxylabs' Web Scraper API plans

As published on oxylabs.io/products/scraper-api/web/pricing, checked 2026-09-17. Enterprise is priced on request. Their docs say the AI assistant sources render JavaScript by default; the pricing page lists no separate price for them.

Price per request

Oxylabs figures are per result on its Micro plan. 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 Oxylabs is stronger

• The same plan covers 100+ pre-configured targets and any website through its universal source.
• Their product page claims 175M+ residential IPs and 20M+ mobile IPs.
• Google geo_location accepts coordinates and criteria ids, and batches of up to 5,000 jobs can be delivered to cloud storage.

Choose this API for AI visibility including Copilot and Grok, with US state targeting, synchronous or async requests on every engine, and a price stated per engine. The guide below maps an Oxylabs job to a task here.

Which to pick

Pick Oxylabs when AI answers are one of many scraping targets you already run through its Web Scraper API, when you need hyperlocal Google targeting by coordinates, batches of thousands of URLs delivered to cloud storage, or its proxy network for sites no structured API covers.

Pick this API when the job is AI visibility: prompts sent to the AI assistants, plus Google Search with the AI Overview, in chosen countries and US states, stored as documented fields. It covers Copilot and Grok, the two assistants Oxylabs’ docs don’t list.

Sources vs engines

An Oxylabs request names a source: google_search, chatgpt, perplexity, gemini, google_ai_mode, or universal for any URL. Every source shares the same job envelope: geo_location, parse, render, callback_url, storage options. Parsed output is source-specific and flagged with a parse_status_code (checked 2026-09-17 on developers.oxylabs.io).

A request here names an engine by endpoint (/v1/monitor/chatgpt) or by taskType (CHATGPT). There are no parse or render flags: every response is structured JSON, with the schema in the API reference.

What this means for a migration:

1. No parse status to check. A task either completes with its parsed result or fails, uncharged.
2. Sync where you want it. Oxylabs’ AI sources are Push-Pull only. Here any engine can be called synchronously for interactive features, at a small surcharge, or queued as a task.
3. Geo is narrower but explicit. Oxylabs’ Google source accepts cities, states, coordinates and criteria ids; its AI sources take a country. Here the assistants take a country and a US state; Google Search takes location (City,Region,Country), uule, hl and device.

Migration: a ChatGPT job with a callback

On Oxylabs

Their ChatGPT docs show a Push-Pull job with basic auth, a prompt, parsing, a country as geo_location, and a callback URL (checked 2026-09-17, developers.oxylabs.io):

curl -X POST https://data.oxylabs.io/v1/queries \
  -u "$OXYLABS_USER:$OXYLABS_PASS" \
  -H "Content-Type: application/json" \
  -d '{
    "source": "chatgpt",
    "prompt": "best project management tool for construction firms",
    "parse": true,
    "geo_location": "United States",
    "callback_url": "https://your-app.com/oxylabs-callback"
  }'

The callback tells you the job is done; results are then fetched from the job’s results endpoint (type=parsed). Their docs describe an optional search flag that turns on web search for this source, off by default.

On this API

curl -X POST https://api.answerline.dev/v1/async/task \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "taskType": "CHATGPT",
    "payload": {
      "prompt": "best project management tool for construction firms",
      "country": "US",
      "include": { "markdown": true }
    },
    "idempotencyKey": "pm-construction-US-2026-09-17",
    "webhook": { "url": "https://your-app.com/hooks/answers" }
  }'

The webhook delivery carries the result itself, so there is no second fetch. Web search is forced by default; disableWebSearch: true lets ChatGPT decide on its own, and sources can then be empty.

Field mapping

On this API the four flags rawResponse, searchQueries, ads and shopping form one group: enabling any of them adds 2 credits once, however many you enable.

Google Search and AI Overviews

Oxylabs returns AI Overviews inside google_search results when you enable rendering; its docs describe this as maximizing the chance of getting one. Here the AI Overview is an explicit add-on:

import os, requests

r = requests.post(
    "https://api.answerline.dev/v1/monitor/google",
    headers={"Authorization": f"Bearer {os.environ['API_KEY']}"},
    json={
        "query": "construction project management software",
        "country": "US",
        "location": "Denver,Colorado,United States",
        "device": "desktop",
        "include": {"aioverview": {"markdown": True}},
    },
    timeout=330,
)
result = r.json()["result"]
aio = result.get("aioverview")
print("AI Overview shown" if aio else "No AI Overview", len(result["organicResults"]))

aioverview is null when Google didn’t show one. When it is present, sources holds the source rail and citationPills the inline chips, which lets you separate “cited in the answer text” from “listed in the rail”.

Batches and throughput

Oxylabs’ batch endpoint takes up to 5,000 queries per call. This API’s batch takes up to 500 tasks per call, and each task is admitted on its own: an overflowing queue rejects the whole batch with 429 QUEUE_LIMIT_EXCEEDED, otherwise items fail individually. A 5,000-prompt run is ten batch calls with the same idempotency key scheme.

How many tasks run at once is set by your plan’s concurrency. Tasks wait in your queue for a free slot; GET /v1/async/status shows queued and processing counts. See rate limits.

Cost comparison approach

Oxylabs charges per result, with the rate depending on target and rendering, on monthly plans with an included result count. The pricing page lists no separate rate for AI sources. This API charges credits per engine; ChatGPT and Copilot tasks are 5 credits, Grok and Gemini 4, Google Search 3 plus add-ons.

1. Ask Oxylabs which rate applies to the AI sources you use, since the pricing page does not say.
2. Count answers per engine and per market.
3. Account for billing rules: Oxylabs bills 4xx results as successful; here failed tasks are free.
4. Compare the cost of the results you can use, not results returned. An Oxylabs result with a parse failure, or a Google result without the AI Overview you needed, costs the same as a good one.

Running both side by side before cutting over

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

1. Choose prompts for the assistants both sides cover, plus Google Search queries where you track AI Overviews.
2. Keep the Oxylabs Push-Pull jobs as they are, with the same geo_location countries.
3. Submit matching tasks here with country set to the same country and a webhook per task.
4. Write both into one table: provider, engine, market, prompt, answer text, cited domains, parse status on Oxylabs, task status here.

What to compare at the end of the run:

• Usable-result rate: Oxylabs results with a successful parse status versus COMPLETED tasks here.
• AI Overview presence on the same Google queries, market and device.
• Cited domains per prompt, compared against day-to-day variation on one provider.
• Billing: what you paid for results you couldn’t use on each side, given that Oxylabs bills 4xx results.

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

Oxylabs reports job status (pending, done, faulted) and a parse status code per result, bills 2xx and 4xx results and not 429 or 5xx, per its billing docs.

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. Copilot or Grok needed? Not in Oxylabs’ docs; covered here.
2. Synchronous AI answers? Only possible here.
3. Coordinates or Google criteria ids? Only on Oxylabs; here use location or uule.
4. Non-AI scraping on the same contract? Oxylabs.
5. Per-task webhooks with signatures and idempotency? This API.

Pitfalls

• Keeping the two-step fetch. Oxylabs callbacks announce completion; deliveries here carry the data. Remove the results fetch or you’ll call an endpoint that doesn’t exist.
• Free-text geo. Oxylabs warns that an unrecognised Google geo_location is not rejected. Here country is an ISO 3166-1 alpha-2 code; list the codes an engine supports with GET /v1/countries once and cache them.
• Prompt length. Oxylabs documents a 4,000-character limit for its ChatGPT source. Keep prompts to what a user would type; long pasted context measures something else.
• Retry storms. Don’t resubmit a task that is still QUEUED or PROCESSING. Only COMPLETED and FAILED are final, and a repeated idempotency key answers 409 anyway.

Start with the quickstart or the Copilot engine page.

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