Agent-Ready Product Data
14+
Years in ecommerce
210+
Shopify stores built
$1.5B+
In client GMV
Global
LA / LON / MEL
Machines compare facts. Give them yours.
We organise Shopify product data so customers and the systems reading your catalogue can find clear, consistent facts: sizes, materials, compatibility, prices and availability.
The work starts at the source, in Shopify metafields, your PIM or CMS. We map the attributes, check variants and connect the information to your product pages, schema and feeds.
People define the model and review exceptions. AI helps us extract and check information at scale; it does not turn a guess into a product fact. Human taste. AI pace.
What we build
Attribute modelling
Decide which facts matter to your buyers, where each fact lives and how variants differ. Model them consistently in Shopify metafields, Sanity or your PIM.
Accurate Product schema
Publish relevant product and offer markup that matches the page and your source data. Include identifiers, prices, availability and review information where applicable, then validate the output.
Variants and availability
Keep product options, SKUs, prices and stock aligned across the storefront and connected channels. Check the rules for delivery costs and returns rather than assuming every channel reads them the same way.
Feeds and sync
Connect the data to the feeds and channels you use, including Shopify Catalog where eligible. Keep it aligned through systems and integrations.
Shopify or Die
Insights into the current and future state of Shopify Plus commerce. Headless architecture, agentic commerce, integration strategy, and the engineering decisions behind stores that scale.
One dataset, three payoffs
The same product information supports your site search and filters, product pages and eligible AI shopping channels. Clear facts also support AI search work; accurate data alone does not guarantee a recommendation or sale.
For the rest of the site, content architecture helps keep capabilities, buying answers and internal links clear and consistent.
Frequently Asked Questions
What product data do AI agents need to complete a purchase?
Relevant attributes such as size, material, dimensions and compatibility; accurate variants, prices and availability; and clear delivery and returns information. The purchase also depends on the channel’s supported checkout, eligibility and permissions. We test the actual journey rather than treating complete data as proof that checkout works.
What does agent-ready actually mean?
Here it means product information that a supported AI channel can retrieve and represent accurately, with the buying journey tested for that channel. It is a practical description, not a certification or guarantee that an assistant will recommend the product.
Is this just schema markup?
No. The work starts with the source data: where facts live, how attributes and variants are modelled, and how updates reach the store and feeds. Schema is one output, and it needs to match the visible page.
We have thousands of SKUs. How does this scale?
We design a reusable attribute model, use bulk processing and automate extraction where reliable. People review uncertain values and exceptions before changes are approved. The process is designed to keep working as the catalogue grows.
Where should product data live?
That depends on your catalogue and systems. Shopify metafields suit many stores; a PIM can help across multiple channels, while Sanity can support content-heavy headless builds. We recommend the simplest suitable source of truth and plan the connections around it.