Product data is the bottleneck. We got tired of watching it.

Building TDCCommerce meant onboarding a lot of catalogs. Every implementation followed the same shape: the software went in quickly, and then everything stopped for months while somebody worked through product data.

Not because the data was complicated. Because there was so much of it, and because every SKU needed a small amount of research that nobody could justify doing forty thousand times. Teams solved it the only way available — with people, offshore, slowly, and usually without ever checking whether the result was correct.

The second half of that is the part that stayed with us. Catalogs were being filled at enormous cost and then never audited. A specification typed in 2019 was treated as true forever, because there was no practical way to ask the question again.

So Catalog AI does both halves. It fills the gaps, and it goes back and checks. And because a value you cannot verify is a value you have to re-check by hand, everything it produces carries the source it came from and a score for how confident it is.

It runs inside TDCCommerce for teams on the unified platform, and it runs on its own for everyone else — because the catalog problem does not care what you replatformed to last year.