AI-driven completeness scoring and error detection across your entire catalogue — in real time. Know exactly what's publish-ready, what needs enrichment, and what's blocked before anything reaches your PIM or storefront.
.png)
Three layers of quality intelligence — completeness scores, error detection, and publish readiness — all connected to the tools that fix problems when they're found.
Every product gets a percentage score based on your schema's required and optional fields. Filter your catalogue by score. See what needs attention before it causes problems downstream.
AI identifies values that are out of range, in the wrong format, statistically unlikely, or conflicting with other attributes. Flagged before they reach your PIM or any channel.
A binary gate based on your own rules. Products above your completeness threshold are marked ready. Everything else is held back — automatically. No manual review of 10,000 rows.
Completeness is calculated against your own required and optional field definitions — not a generic standard. A product missing an optional image scores differently from one missing a required voltage. You decide the weighting. AI tracks it across your entire catalogue in real time.
.png)
Completeness tells you what's missing. Error detection tells you what's wrong. AI applies statistical analysis and business rules across every attribute — flagging values that are out of range, in the wrong format, or inconsistent with related fields.
.png)
Set a completeness threshold — say, 90% — and only products that meet it are eligible for export to your PIM, ERP, or channels. No manual review of 10,000 rows. No incomplete products slipping through to your storefront.
.png)
Data Structure is one of three pillars.
Book 30 minutes. We'll run a quality audit on a sample of your products and show you exactly what's blocking publish readiness.
Product data enrichment that actually gets done — so your product pages convert, your search works, and your team stops living in spreadsheets.
.png)
