Track LLM Citations Across Every Model

The Problem

Your brand might be cited by ChatGPT, ignored by Perplexity, and cherry-picked by Gemini in the same hour. Without a single view across engines, marketing teams fly blind on which prompts surface the brand, which competitor is eating their share of voice, and whether a content push actually moved the needle in generative answers.

The Scavio Solution

Scavio's agentic search exposes each major LLM engine (ChatGPT, Perplexity, Gemini, Claude, You.com) through the same request shape. One API call per (prompt, engine) returns the cited URLs, the answer text, and the position of each citation. Wire the endpoint into a cron and you have multi-engine citation tracking with zero custom scrapers.

Who It Is For

Marketing leads and AEO practitioners who need a single pane of glass for LLM brand visibility.

Key Benefits

• One schema across ChatGPT, Perplexity, Gemini, Claude, You.com
• Per-prompt citation lists with URL, anchor text, and answer position
• Diff-ready output for day-over-day change detection
• No LLM subscriptions or API keys needed on your side
• Pairs with agentic-traffic pixel for full AEO observability

Python Example

import os, requests
SCAVIO = os.environ['SCAVIO_API_KEY']
H = {'x-api-key': SCAVIO}

def track(prompt):
    engines = ['agentic-chatgpt', 'agentic-perplexity', 'agentic-gemini', 'agentic-claude']
    out = {}
    for e in engines:
        r = requests.post('https://api.scavio.dev/api/v1/search',
            headers=H, json={'platform': e, 'query': prompt}).json()
        out[e] = r.get('citations', [])
    return out

print(track('best serp api 2026'))

JavaScript Example

const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'content-type': 'application/json' };
const engines = ['agentic-chatgpt', 'agentic-perplexity', 'agentic-gemini', 'agentic-claude'];

async function track(prompt) {
  const out = {};
  for (const e of engines) {
    const r = await fetch('https://api.scavio.dev/api/v1/search', {
      method: 'POST', headers: H,
      body: JSON.stringify({ platform: e, query: prompt })
    }).then(r => r.json());
    out[e] = r.citations || [];
  }
  return out;
}

Platforms Used