Ready for AI Agents
When an AI agent buys on behalf of a human, it needs to find your price, parse your terms, and compare you cleanly. Neurock structures your product data and architecture so machines can choose you.
How it Works
No black boxes. Here is the actual mechanism behind the result.
Agentic readiness audit
We test how AI agents currently find, parse, and evaluate you across the platforms where machine-mediated buying is starting to happen.
Product data structuring
We structure pricing, specifications, availability, and service levels so an agent can read them without ambiguity. If a machine cannot find your price, it cannot choose you.
Schema implementation
We implement Product, Offer, Organization, and FAQ schema so agents understand exactly what you sell and on what terms.
Comparison architecture
We build the comparison pages agents reach for when a buyer asks them to evaluate options, so you are present at the decision, not after it.
Deep-link accessibility
We make sub-answers individually addressable, so an agent can link directly into the precise detail it needs to justify choosing you.
What’s included
- An agentic readiness audit across active AI agent platforms
- Product data structuring for machine parsing: pricing, specs, availability, SLAs
- Schema implementation: Product, Offer, Organization, FAQ
- Comparison page architecture for agent-driven decision queries
- Technical accessibility for deep linking into sub-answers
E-commerce and B2B brands whose buyers are starting to delegate research and purchasing to AI agents.
Get my free AI visibility auditCommon Questions
We spend most of our time understanding what clients sell, who buys it, and where the friction sits. The same questions come up in almost every one of those conversations, so we have answered them here.
Agentic commerce is buying mediated by AI agents acting on behalf of humans. It spans agent-to-agent (A2A), agent-to-human (A2H), and human-to-agent (H2A) interactions, where a machine does the research, comparison, and sometimes the purchase itself.
B2B procurement is moving toward agent-mediated sourcing, and consumer assistants increasingly complete tasks end to end. Brands whose product data is not machine-readable simply will not be considered, regardless of how good the product is.
An agentic readiness audit, structured product data for machine parsing, Product and Offer schema implementation, comparison page architecture, and deep-link accessibility, delivered as an initial buildout plus ongoing optimization.
An initial buildout followed by a monthly retainer, scoped to your catalog and the platforms involved. Every engagement starts with a discovery call, and we share pricing there once the scope is clear.
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.