Create
Map source-shaped listing data into canonical product facts with identifiers, variants, price, availability, and policy context.
AI commerce data fabric
When a listing is created, make it ready for AI commerce.
KoreLens gives platforms and marketplaces an SDK-first path: when a seller creates or edits a listing, call KoreLens with the source-shaped product payload. KoreLens normalizes the data, raises missing-field requests, preserves authority history, and prepares the catalogue for OpenAI-style product feeds, Merchant Center workflows, and future agent checkout patterns.
Readiness and proof, not guaranteed placement. Platform approval and ranking decisions stay with each platform.
Illustration with fictional products — not a live model answer. It shows the mechanism: assistants can only present products whose data they can read and verify. Listing and in-chat checkout are approval-dependent and decided by each platform.
SDK sync for Shopify, WooCommerce, Amazon-like listings, and merchant feeds
Webhook-first ingestion for listing-created and listing-updated events
Governed entity pricing instead of raw API-call pricing
No claim of platform approval until a real integration verifies it
Operating layer
From visibility gap to governed proof.
Request
If the listing is missing GTIN, image, return policy, stock, or checkout data, raise a product-level data request.
Charge
Price by governed products, listings, environments, and automation depth so high-volume platforms expand revenue with usage.
Why it compounds
The developer moat is embedded creation: KoreLens sits inside listing workflows and becomes the system of record for AI-commerce readiness.