The Problem
Research teams that need data from Google, Amazon, YouTube, Reddit, and Walmart maintain separate scrapers, API clients, and parsing logic for each source. Each integration breaks independently, requires its own authentication, and returns a different schema. The overhead of maintaining 5 data pipelines dwarfs the time spent actually analyzing the data.
The Scavio Solution
Scavio unifies all five platforms behind a single POST endpoint. Change the platform parameter to switch sources. The response schema is consistent across platforms -- organic results always have title, link, snippet, and position. Platform-specific fields (price for Amazon/Walmart, view count for YouTube) are added on top. One API key, one client, one retry strategy, one monitoring dashboard.
Before
Before consolidation, a market research team maintained separate integrations for Google (SerpAPI at $25/mo), Amazon (Apify actor at $29/mo), YouTube (YouTube Data API with quota management), Reddit (PRAW with rate limiting), and Walmart (custom scraper with proxies). Total: 5 integrations, 3 vendor accounts, 12+ hours/month maintenance.
After
After switching to Scavio, all five data sources work through one API call with a platform parameter. One vendor account, one API key, one response parser. Maintenance dropped from 12 hours/month to near zero. Combined cost at moderate volume: $30/mo for 7,000 credits covering all platforms.
Who It Is For
Research teams, data analysts, and product teams who need structured data from multiple platforms without maintaining separate scrapers and API integrations for each source.
Key Benefits
- One API endpoint covers Google, Amazon, YouTube, Walmart, and Reddit
- Consistent response schema across all platforms
- One API key replaces 3-5 vendor accounts
- Maintenance drops from 12+ hours/month to near zero
- $30/mo for 7,000 credits covers moderate multi-source research
Python Example
import requests, os, json
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def multi_source_search(query: str, platforms: list[str]) -> dict:
results = {}
for platform in platforms:
r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'platform': platform, 'query': query}, timeout=10).json()
organic = r.get('organic', r.get('organic_results', []))
results[platform] = {
'count': len(organic),
'top_3': [{'title': o.get('title', ''), 'link': o.get('link', '')}
for o in organic[:3]],
}
return results
query = 'wireless earbuds 2026'
data = multi_source_search(query, ['google', 'amazon', 'youtube', 'reddit'])
for platform, info in data.items():
print(f'\n{platform.upper()} ({info["count"]} results):')
for item in info['top_3']:
print(f' - {item["title"]}')JavaScript Example
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function multiSourceSearch(query, platforms) {
const results = {};
for (const platform of platforms) {
const r = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: H,
body: JSON.stringify({ platform, query })
}).then(r => r.json());
const organic = r.organic || r.organic_results || [];
results[platform] = {
count: organic.length,
top3: organic.slice(0, 3).map(o => ({ title: o.title || '', link: o.link || '' })),
};
}
return results;
}
const data = await multiSourceSearch('wireless earbuds 2026', ['google', 'amazon', 'youtube', 'reddit']);
Object.entries(data).forEach(([p, info]) => {
console.log(`\n${p.toUpperCase()} (${info.count} results):`);
info.top3.forEach(i => console.log(` - ${i.title}`));
});Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Amazon
Product search with prices, ratings, and reviews
YouTube
Video search with transcripts and metadata
Walmart
Product search with pricing and fulfillment data
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