Perplexity answers API

What the Perplexity API returns

Perplexity cites heavily, and every answer is built from the pages its search finds. Each one comes back read the same way as the other engines: brands in order, every citation typed, and the raw response kept as proof.

The Sonar API vs aivisibilityskill

Perplexity sells its Sonar models through its own API, and you can call it directly. You get back the answer text and the links it used. What you don't get is the reading: which brands it named, in what order and tone, and what kind of site each source is. That's the part this API adds, in the same schema as seven other engines.

Calling Sonar yourself vs through aivisibilityskill

	Perplexity Sonar API	aivisibilityskill
The answer and its links	Yes	Yes
Brands named	You parse them yourself	Listed with rank, recommendation and sentiment
Source types	No	Every citation typed: brand_owned, review_site, media, reddit…
Prices and plans it states	No	Read into facts, with the quote
ChatGPT, Gemini, Google AI and others	No	Yes, in the same call
Schedules, history, webhooks	Build your own	Built in

One honest difference: this is Perplexity's API answer, not the perplexity.ai app. The app lets people pick models and modes, so their answers can differ from the API's. For a fresh question with default settings, the API answer is the closest consistent measure.

One question, three different answers

We asked “best CRM for early-stage startups” on each engine from the US on the same morning. Each card is what the API returned: how the answer opens, the brands it named in order, and the first sites it cited.

Where each answer ranks each brand (1 = named first; – = not named)

Brand	Perplexity	ChatGPT	Google AI Overview
HubSpot	1	2	1
Less Annoying CRM	2	– not named	– not named
Attio	3	1	3
Pipedrive	4	3	2
Zoho CRM	5	4	5
Bigin	6	– not named	– not named
Salesforce Starter	7	– not named	– not named
Close	– not named	5	– not named
Ringy	– not named	– not named	4
Salesforce	– not named	– not named	6 (to avoid)

All three name HubSpot, Attio and Pipedrive. Perplexity names 10 brands in all, including Less Annoying CRM and Capsule, which neither ChatGPT nor the AI Overview mention. It shares three sources with ChatGPT (techradar.com, hackceleration.com and attio.com) and one with the AI Overview (ringy.com).

Perplexity citations

For the CRM question, Perplexity cited 17 links from 15 sites, more than any other engine we asked (ChatGPT cited 10, the AI Overview 6, AI Mode 3), and named 10 brands, also the most. Each citation comes back with its position, URL, title and source type, so you can see which roundups and vendor pages Perplexity relied on, and whether your customer's site is one of them.

Track brand mentions in Perplexity

Put a brand, its competitors and its buyers' questions in a project with a daily or weekly schedule. The API returns how often Perplexity names the brand (with error bars), each competitor's share, the sites Perplexity cites and the history, and a webhook tells your server when each run is done. Track it next to ChatGPT and Google AI Overviews in the same project.

Call the Perplexity API from TypeScript or Python

The SDKs wrap the same request, retry safely without charging twice, and wait for the answers for you. Free sandbox keys (aiv_test_…) return realistic sample answers, so you can build the whole feature before spending a credit.

TypeScript (npm install @aivisibilityskill/sdk)

import { Aiv } from "@aivisibilityskill/sdk";

const aiv = new Aiv({ apiKey: process.env.AIV_KEY! });

const job = await aiv.checks.create({
  questions: ["best CRM for early-stage startups"],
  engines: ["perplexity"],
  locale: "en-US",
});
const done = await aiv.jobs.wait(job.id);

for (const answer of done.answers ?? []) {
  console.log(answer.brands?.map((b) => `${b.rank}. ${b.name}`));
  console.log(answer.citations?.map((c) => c.domain));
}

Python (pip install aivisibilityskill)

import os
from aivisibilityskill import Aiv

aiv = Aiv(api_key=os.environ["AIV_KEY"])

job = aiv.checks.create(
    ["best CRM for early-stage startups"],
    engines=["perplexity"],
    locale="en-US",
)
done = aiv.jobs.wait(job["id"])

for answer in done["answers"]:
    print([(b["rank"], b["name"]) for b in answer["brands"]])
    print([c["domain"] for c in answer["citations"]])

For thousands of questions, send them as one batch of up to 20,000 answers and get one webhook when it's done. Full guides: SDKs, API reference, OpenAPI 3.1 spec.

Prefer a ready-made tool? llm-brand-tracker on GitHub tracks your brand against competitors on all 8 engines every week, free on GitHub Actions. Free and MIT licensed.

Perplexity API pricing

You pay per answer, in credits. Perplexity is asked live, one call per answer, so there's one speed. A dollar buys 1,000 credits on a pack; monthly and volume plans include more. An answer reused from a recent identical one (max_age_hours) costs half, and an answer that fails costs nothing.

Every account gets the same API and every engine, starting with 500 free credits and no card. Volume plans start at $500 a month for 750,000 credits, with invoicing and a 99.5% uptime commitment: see volume plans.

Countries and languages

Perplexity is asked through its API, so it isn't answering from a location. For any locale other than en-US, it's told which country the buyer is in, for any of 250 countries and territories, and it answers in the question's language (de-DE, pt-BR, ja-JP…). The app and search engines answer from the country itself: ChatGPT in 192, Gemini, Google AI Overviews and AI Mode in 240. GET /v1/locales lists every pair for free.