Use case

Make your products legible to buying agents

When software does the buying, a product that cannot be parsed, priced, and verified is a product that cannot be bought.

The problem
What is actually happening

An agent is doing the shopping, and it cannot read our catalogue

Agentic commerce removes the human who used to compensate for a confusing page. An agent needs the product, its attributes, its price, its availability, and its terms in a form it can read without inference. Anything ambiguous is either skipped or, worse, represented wrongly on your behalf.

How we fix it
The work

What the engagement involves

  • Audit what an agent can actually read on your product and category pages, as opposed to what a person can see.
  • Implement valid, complete product structured data so attributes and terms survive machine extraction.
  • Remove the ambiguities that cause an agent to misstate a price, a variant, or a condition.
  • Re-test with the agent behaviour itself, not with a validator alone.
OUTCOME Your catalogue is readable, comparable, and safe to quote for the software increasingly doing the purchasing.
Agentic Commerce

Find out where you stand

When a buyer asks an assistant who to work with, it names two or three companies and moves on. The audit puts the questions your buyers actually ask to all five AI platforms, scores you on the five things a model weighs before it cites anyone, and shows you which competitor is named in your place. You get the gap and the order to close it in, five business days from briefing.