The AI commerce layer
Products deserve better answers.
AgentShelf turns the static catalog into a living product story—structured for the way AI assistants actually help people shop.
Start with what you have
Every catalog has a story hiding in it.
Bring in your product data and AgentShelf finds the signals an AI shopper needs to make a confident recommendation.
Find the opportunity
See exactly what the AI cannot see.
Readiness scoring turns vague content gaps into a clear, prioritized path forward—starting with the SKU that needs you most.
Make the lift
One product. A much better answer.
Add context, personas, use cases, and proof points in one focused pass. The product becomes easier to understand and easier to recommend.
Show the difference
Better content. Measurable impact.
Test the same shopper prompts before and after enrichment, then export the profile your AI stack can use.
Open evidence lab →From demo to deployment
A recommendation layer brands can actually adopt.
Keep existing catalog systems. Add an AI-ready layer with traceable content, repeatable evaluation, and a clean handoff to the stack you already use.
CSV, PIM, or CMS fields
Map attributes to a shared schema
Add personas, use cases, and guardrails
Score readiness and simulate intent
Export JSON-LD or send via API
Separate source facts from generated narrative so teams can review before publishing.
Start with CSV export today, then connect PIM, CMS, webhooks, and API delivery without changing the workflow.
Running shoes, skincare, and audio gear can use the same intent-to-evidence loop.
Ready to see it work?