The Problem
Content teams publishing at volume cannot manually fact-check every data point, resulting in articles with outdated statistics, wrong prices, and missing citations.
How Scavio Helps
- Live search data prevents publishing outdated statistics
- Source URLs enable proper citation in every article
- Multi-platform validation catches single-source errors
- Programmatic integration into existing content pipelines
- Cost-effective at $0.005/verification vs $50+/hr manual fact-checking
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
YouTube
Video search with transcripts and metadata
Quick Start: Python Example
Here is a quick example searching Google for "average SaaS churn rate 2026 benchmark":
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 Content marketing teams and AI writing tool developers
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your content data grounding solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.