Solutions · Manufacturers

Your specs, stated correctly, everywhere they appear.

You publish the truth about your products once. Then it gets retyped by a distributor, abbreviated by a reseller, and mangled by a marketplace. Catalog AI shows you where your data has drifted and what your products are actually selling for.

Sound familiar

Three things we hear every time.

  1. 01Resellers publish specifications that do not match the datasheet.
  2. 02Nobody can say what the street price of a given SKU is this week.
  3. 03Product data lives in a spreadsheet that three departments each keep a different copy of.
Workflow

How it runs here

  1. STEP 1

    Load the authoritative record

    Import your product data by CSV or API. This is the version everything else gets measured against.

  2. STEP 2

    Find where it has drifted

    Validation re-checks each attribute against live sources and returns a confidence score with the reasoning and the page it read.

  3. STEP 3

    Watch the market

    Market Analysis reports which retailers list your products, at what price, against what MSRP, and whether they are in stock.

  4. STEP 4

    Correct at the source

    Export the exception list and send it to the channel partners who need it.

Manufacturers

Questions from this side

Does this do MAP enforcement?
It gives you the observation, not the enforcement. Market Analysis reports current selling price against MSRP per retailer; acting on a violation is still your process.
How current is the pricing data?
It is read at the moment the job runs. Every run is stored, so repeated runs give you a movement history rather than a single snapshot.
Can we run this on a schedule?
Trigger jobs on your own schedule through the API and receive a webhook when each one finishes.

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