The Problem
F&B operators rely on expensive consultants or gut feel for market decisions because structured local competitive data is hard to obtain programmatically.
How Scavio Helps
- Local pack data reveals competitor density by area
- Track competitor menu and pricing changes
- Identify underserved cuisines in target neighborhoods
- Monitor review sentiment trends for market opportunities
- Programmatic access for multi-location analysis
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Google Shopping
Shopping results with multi-retailer pricing
Quick Start: Python Example
Here is a quick example searching Google for "best ramen restaurant downtown austin texas":
Python
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 Restaurant operators, F&B chains, and food industry consultants
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your f&b market intelligence 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.