The Problem
Google Analytics ignores LLM agent traffic and most analytics tools bucket it as bot traffic. Teams have no idea which pages answer engines actually fetch, how often, or what queries triggered the fetch. AEO optimization is flying blind without agent visit data joined to citation data.
How Scavio Helps
- Identify which pages answer-engine crawlers actually load
- Correlate agent visits with citation queries from Scavio ask
- Detect new LLM user agents as engines evolve
- Spot referral patterns between citation and visit
- Normalized event log fits any warehouse or dashboard
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Quick Start: Python Example
Here is a quick example searching Google for "user-agent perplexitybot on /blog/serp-api":
import requests
API_KEY = "your_scavio_api_key"
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={
"x-api-key": API_KEY,
"Content-Type": "application/json",
},
json={"query": query},
)
data = response.json()
for result in data.get("organic_results", [])[:5]:
print(f"{result['position']}. {result['title']}")
print(f" {result['link']}\n")Built for AEO specialists, site owners, content strategists, technical SEO
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your agentic traffic logging solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.