First to Market
The Data Layer for AI Shopping Agents
AI shopping agents can only be as accurate as the product data they call on. kwery is GTIN-matched, confidence-scored pricing across 12 marketplaces — built to be a single, reliable tool call, not another scraped feed an agent has to second-guess.
Live across marketplacesLive across marketplaces · Billions of prices monitored monthly
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The Gap
What Merchant Agents Can't See
Merchant agents can decide. They can't see the market.
Merchant agents can read a retailer's own sales performance, stock levels, and order history, and draft pricing, promotion, and campaign changes from that data. What they can't see is the market outside the store — what a competitor is charging right now, or whether a listed price is even still current. An agent can draft a confident price change and still be wrong the moment it's compared to reality. kwery is the tool call that closes that gap — three things every price-data result needs, that most feeds don't provide:
Verified identity
GTIN-matched, not keyword-guessed, so the agent has the actual product, not something similar.
A confidence score per result
Identity, completeness, price integrity, offer contamination, and freshness, scored individually, so an agent can weigh how much to trust an answer instead of treating every result as equally reliable.
A live, on-demand result
Fetched at the moment of the call, not read from yesterday's crawl.
{
"trust": {
"score": 0.92,
"detail": {
"identity": 1.00,
"completeness": 0.89,
"price_integrity": 0.95,
"offer_contamination": 0.97,
"freshness": 0.75
}
}
}Breadth
One Tool Call, 12 Marketplaces
Every marketplace, one schema.
An agent can't predict which product a shopper will ask about next. kwery covers Amazon, Google Shopping, eBay, Walmart, Idealo, Otto, Kaufland, Billiger, Guenstiger, Lidl, AliExpress, and Rakuten — one schema, one credential, no separate integration per source.
Amazon
Pricing, Buy Box, offers, ratings, and seller data across 20+ Amazon marketplaces.
Google Shopping
Live comparison prices and merchant listings across 48 supported markets.
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ebay
Offers, sold listings, bidding data, and seller analytics from 18 ebay markets.
Walmart
Real-time prices, availability, and seller data from Walmart US and Canada.
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Idealo
Full merchant offers, price comparisons, and ranking data across DACH and Europe.
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Otto
Product pricing and marketplace data from Germany's largest non-Amazon retailer.
Try It
Ready to point an agent at live market data?
Start free with 1,000 credits. No credit card. One endpoint, every source.
Why kwery
Built for One Request, One Answer
One synchronous call. A live result, not a cached one.
Most price-data APIs are built for bulk jobs — submit thousands of SKUs, poll, download later. An agent making a decision mid-conversation can't wait on a queue. kwery's wait parameter holds the request open and returns a single synchronous result in one call — no polling, no job ID to track.
Every result is fetched at the moment of the request, not read from a cached snapshot with a timestamp attached — the freshness score returned with each result reflects that in real time.
One call in. One matched product, with its confidence score, back before the agent's next step.
curl -s https://api.kwery.co/job \
-H "Authorization: Bearer $KWERY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"source":"amazon","country":"de","key":"gtin","values":["4006381333962"],"wait":true}'Early Use Cases
Who's Building With This
Three ways teams are wiring in AI-ready price data.
Early adopters are using kwery in three ways:
Retailers building their own shopping assistant
Feed live competitor and catalog pricing into a customer-facing agent without maintaining a separate data pipeline.
Feeds → customer-facing agent
Marketplaces and comparison tools building AI-driven search
GTIN matching means the agent compares the same product across sources, not similarly-titled listings.
Feeds → AI search index
Teams building merchant agents
A staff-facing agent that drafts pricing and promotion changes needs to know what the market is doing, not just what's in the retailer's own sales data. Ready to wire this in? Read the integration guide →
Feeds → merchant agent
No Signup Needed
Try It Before You Wire It Up
Prototype first. Go live when you're ready.
kwery ships a mock server that returns real response shapes with no API key and no credits consumed — prototype a tool definition, test how your agent handles the response, then swap in a live key when you're ready for production.
curl -X POST https://docs.kwery.co/_mock/openapi/job \
-H "Authorization: Bearer test123" \
-H "Content-Type: application/json" \
-H "x-redocly-response-body-example: wait" \
-d '{"source":"idealo","country":"de","key":"gtin","values":["4006381333962"]}'Self-Serve
One Credit. One Resolved SKU
Product matching, product page, and offers — billed as a single credit.
Product Matching
Identify the correct product within the requested source using GTIN or URL.
Product Page
Title, brand, specs, images, and category — fully normalized.
Offers
Every seller, price, condition, and shipping option in the offer section.
Entry Price
€399 / mo
Included
100k credits / mo
Overage
€3.99 / 1k credits
1,000 free credits on signup — no credit card required.
Support
Common Questions
What teams ask before wiring kwery into an agent's tool-calling layer.
Browse all FAQsNo — kwery is a REST API your team calls from your own agent's tool-calling layer, giving you control over which results the agent sees and how they're used.
Yes — see the integration guide for a worked example.
Yes, via the wait parameter (up to 50 seconds, synchronous).
Every kwery result is fetched live at request time and carries a confidence score — not a static snapshot with a timestamp attached.
Give Your Agent Data It Can Trust
GTIN-matched, confidence-scored pricing across 12 marketplaces — one tool call, one answer.