Extract Product Data at Scale

The Problem

Pulling product data from Amazon and Walmart at scale means juggling throughput, freshness, marketplace coverage, and legal-grade access policies. In-house scrapers cap out quickly because every marketplace throttles differently, every region has its own anti-bot profile, and every category has its own schema quirks. A spreadsheet of five hundred ASINs is manageable. A pipeline feeding a repricer, a catalog builder, or a pricing intelligence product across five marketplaces is not, at least not without dedicated infrastructure that most companies should not be building.

The Scavio Solution

Scavio handles marketplace coverage, throttling, and schema normalization for you. You batch queries through a simple REST endpoint, we handle concurrency internally, and results come back normalized so the same code path works whether you are pulling Amazon US, Amazon DE, or Walmart. Categories, prices, ratings, review counts, sponsored flags, and seller identity are all first-class fields. You can run millions of product lookups per day without operating a single browser, proxy, or parser on your side. Scale becomes a billing question rather than an engineering question.

Who It Is For

Pricing intelligence startups, catalog aggregators, and retail analytics teams. Anyone whose data pipeline depends on pulling tens of thousands of product records a day without running their own scraping infrastructure.

Key Benefits

• Millions of product lookups per day from a single API key
• Normalized schema across Amazon and Walmart marketplaces
• Sponsored flags, seller ID, Buy Box, and variations included
• Batch-friendly endpoints for parallel extraction workflows
• Consistent performance at one request per second or one thousand

Python Example

import requests
from concurrent.futures import ThreadPoolExecutor

API_KEY = "your_scavio_api_key"

def fetch(asin: str):
    r = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": "amazon", "query": asin, "type": "product"},
        timeout=15,
    )
    return asin, r.json().get("product", {})

asins = ["B0C1234567", "B0C7654321", "B0C9999999"]
with ThreadPoolExecutor(max_workers=10) as pool:
    for asin, product in pool.map(fetch, asins):
        print(asin, product.get("title"), product.get("price"))

JavaScript Example

const API_KEY = "your_scavio_api_key";

async function fetchProduct(asin) {
  const r = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST",
    headers: {
      "x-api-key": API_KEY,
      "content-type": "application/json",
    },
    body: JSON.stringify({ platform: "amazon", query: asin, type: "product" }),
  });
  const data = await r.json();
  return { asin, product: data.product ?? {} };
}

const asins = ["B0C1234567", "B0C7654321", "B0C9999999"];
const results = await Promise.all(asins.map(fetchProduct));
for (const { asin, product } of results) {
  console.log(asin, product.title, product.price);
}

Platforms Used