Agentic Commerce Ready
AI assistants now recommend products Structured data gets you quoted.
WISEPIM gives every SKU schema.org structure, a validated GTIN and machine-readable specs, so ChatGPT, Gemini, Perplexity and Claude can surface it.
Key features
Data AI agents can actually read
ChatGPT, Gemini, Perplexity, Claude: they read structured data, not marketing copy. WISEPIM's output meets the standard each major agent expects.
4agents covered
Validated GTINs, complete attributes
Every SKU passes Quality Guard before publish: valid GTIN, schema-complete attributes, machine-readable specs. Everything an agent needs to recommend your product.
Built on schema.org Product
Output that maps cleanly to schema.org Product, Offer, and Organization: the structured data format AI agents and search engines both rely on.
Specs agents trust, not sales copy
AI agents compare on facts: dimensions, materials, compatibility. WISEPIM turns vague descriptions into clean, typed attributes built for machines to read.
Why now
Why agent-ready data matters now, not later
Discovery is moving from a search box to an assistant that reads catalogs directly. Three things change for the catalogs it can read.
Discovery is shifting from search to agents
Consumers are starting to ask ChatGPT, Gemini, and Perplexity for product recommendations directly. The catalogs agents can read and trust will win that channel, the same way fast mobile sites won the smartphone wave.
Agents shop differently than humans
An assistant comparing a shortlist does it on typed attributes such as dimensions, materials and compatibility, not on hero images and brand storytelling. A catalog without machine-readable specs has nothing to compare.
Marketplace operators are an early signal
Marketplace operators are restructuring catalogs to be machine-readable before their sellers are. Brands that sell through those platforms feel the requirement first; direct retailers get the same request later.
Clean Categorization
A category tree an agent can walk
WISEPIM auto-assigns each product to a clean, consistent category tree, so AI shopping agents can browse, filter, and compare your catalog the way a shopper would.
Side by side
How agents read the same product
The same product, presented two ways. Only one shows up in agent-driven discovery.
| What an agent looks for | Marketing copy only | Agent-ready data |
|---|---|---|
| Structured data | Free-form HTML | schema.org Product / Offer / Brand |
| Product identifiers | Sometimes a SKU | Validated GTIN / EAN / UPC, GS1-registered |
| Attribute coverage | Whatever the copywriter included | Category-complete, machine-readable |
| Image alt text | Decorative or empty alt text | Descriptive, attribute-bearing alt text |
| Trust signals | Review ratings (if scraped) | Aggregated review schema, return policy, brand identity |
FAQs
Questions before you prioritise this
What agent-ready data actually requires, and what it does not fix.
Still have questions?
Can't find the answer you're looking for? Please get in touch with our team.
Contact SupportNext step
Make every SKU agent-ready by default
Run a sample of your catalog through WISEPIM and see what changes when the output carries schema.org structure, validated GTINs and typed specs. The same enrichment feeds your SEO and marketplace exports.
