Forty suppliers. Forty formats. One usable catalog.
Every supplier sends product data a different way, and none of it matches your schema. Catalog AI reads whatever arrives, normalises it against the attributes you define, and fills in what the supplier left out.
Sound familiar
Three things we hear every time.
- 01A new supplier means a new spreadsheet layout and a week of remapping columns.
- 02Half the range never gets listed because nobody had time to write descriptions for 6,000 SKUs.
- 03The same product appears three times under three part numbers, and nobody is sure which one is right.
The agents that matter most here
All six are available on every account. These are the ones this kind of catalog leans on.
How it runs here
- STEP 1
Drop the supplier file in
AI Import reads the PDF, spreadsheet, or price list and extracts products for review before anything touches your catalog.
- STEP 2
Normalise against your schema
Attribute Sets define the fields every product must carry. Enrichment fills the gaps from manufacturer sources and product pages.
- STEP 3
Check before you list
Validation scores each attribute so you can publish the confident rows and route the rest to a human.
- STEP 4
Push it downstream
Export CSV for your PIM or storefront, or let the API write straight into it.
Questions from this side
Can it handle a supplier price list that is really just a PDF of a table?
We carry products from brands that barely have a website. What then?
Can we keep separate catalogs per supplier?
Test it on the part of the catalog that hurts.
Free credits on signup, no card. If it does not hold up on your worst products, you have lost an afternoon.
5 credits on signup · no card required