The Problem
Users want to ask 'find me the best wireless earbuds under $100' and get a curated answer backed by real Reddit reviews. Building this requires real-time product data from multiple marketplaces plus community sentiment.
How Scavio Helps
- Natural language product search across Amazon and Walmart
- Compare prices, ratings, and reviews automatically
- YouTube reviews for product sentiment
- Structured data ready for LLM reasoning
Relevant Platforms
Amazon
Product search with prices, ratings, and reviews
Walmart
Product search with pricing and fulfillment data
YouTube
Video search with transcripts and metadata
Community, posts & threaded comments from any subreddit
Quick Start: Python Example
Here is a quick example searching Amazon for "wireless earbuds under $100 with good bass":
# Amazon search has no sort parameter - rows come back in the marketplace's own ranking.
# Use country (us, gb, de, ...) to pick the marketplace.
import requests
API_KEY = "sk_live_your_key"
query = "mechanical keyboard"
response = requests.post(
"https://api.scavio.dev/api/v1/amazon/search",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
},
json={"query": query, "country": "us"},
timeout=60,
)
response.raise_for_status()
data = response.json()
rows = (data.get("data") or {}).get("products") or []
for row in rows[:5]:
print(row.get("title"))
print(" ", row.get("asin"), row.get("price"), row.get("currency"), row.get("rating"), row.get("reviews_count"))Built for E-commerce apps, chatbot developers, AI startups
Scavio takes care of getting the data, so you can focus on building your ai shopping assistant 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.