Check
Upload a product table for feed validation and run the AI agent readiness check — neither needs extra authorization.
Solutions E-commerce & Cross-border
Buyers are asking AI — is your product data ready?
AI shopping channels are becoming a new entry point, and the ticket in is your product data itself: incomplete fields, mismatched prices or an unopened channel mean AI cannot read your products, or reads them wrong. We turn that invisible state into measurable checks.
Who it is for
E-commerce brands (marketplaces and their own stores), cross-border sellers (independent stores / Shopify / Amazon), and agencies managing multiple stores.
Three real pain points
- Product data has no health report: all-caps titles, links inside descriptions, sale prices without an effective window — none of it errors out, but any of it can keep a product out of AI channels or break checkout.
- No way to know whether the channel is open: platforms such as Shopify enable AI agent commerce automatically, yet merchants cannot see their readiness state or what is missing.
- Agencies run dozens of stores, each with different data quality, platform rules and visibility — and can only inspect them one by one.
How the platform solves it
- Product feed field validation: field-by-field diagnosis against the official specs (ACP / Google Merchant Center), reported as "row + field + value + reason + basis", with a column-level summary pointing at the export template that needs fixing.
- AI agent channel readiness: probes /agents.md, the UCP merchant profile and the MCP endpoint, reporting what is missing and how to add it (read-only — no ordering, no cart creation).
- Brand-level AI visibility monitoring: measures how "how is brand X" and "which brand is better" questions surface your brand across engines — always with denominators, and honest labels when there are no samples.
- E-commerce-specific compliance rules: platform quality-score requirements, price display, review manipulation bans and fulfillment claims — with official platform rules clearly separated from industry practice.
Plans
E-commerce industry pack (channel dimension; stacks with category packs such as beauty, baby care or food) plus Standard tier or above
Implementation path
From check-up to re-test in four steps
Fix the data
Work through the issue list; the column summary identifies which problems are solved once at the template level.
Monitor visibility
Build a brand-level question set, sample on a schedule, and track how mentions and citations change.
Re-test and review
Re-test with fixed definitions and report the trend — data quality is verifiable; recommendation is never promised.