The Problem
Company records across systems use inconsistent naming: 'IBM' vs 'International Business Machines' vs 'IBM Corp'. Fuzzy string matching produces false positives. Dedicated entity resolution vendors charge $10,000+/year. n8n workflows need an affordable, reliable way to canonicalize company names.
How Scavio Helps
- Canonical company name via Google Knowledge Graph at $0.005/lookup
- False positive rate drops from 12% to under 1%
- 500 records matched for $2.50 per batch run
- Works as a standard n8n HTTP Request node
- Replaces $10,000+/year entity resolution vendors
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Quick Start: Python Example
Here is a quick example searching Google for "A RevOps team runs an n8n workflow to deduplicate company records between HubSpot and their billing system. Each company name goes through Scavio's Google search to extract the Knowledge Graph canonical name. 'Mercury' resolves to the correct entity based on context (Mercury Financial vs Mercury banking app). 500 records per batch at $2.50. Manual cleanup time drops from 4 hours/week to 15 minutes.":
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 RevOps teams, data engineers, n8n workflow builders, CRM administrators dealing with duplicate company records
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your n8n company data enrichment and matching solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.