Shoppers Have Agents. Your Brand Needs One To Talk To Them.

Shoppers tell AI what they need. Your Brand Agent publishes your enriched product catalog in the machine-readable formats these AI agents read: ACP, UCP, JSON-LD and MCP. This goes across LLMs (ChatGPT, Gemini, Claude), personal AI agents (Meta Muse, OpenAI dots, Instinct) and retailer-owned shopping agents (Walmart’s Sparky, Amazon’s Alexa for Shopping).

An enriched product catalog is formatted into machine-readable formats (ACP, UCP, JSON-LD, MCP) by the Brand Agent to be recommended by agents (ChatGPT, Gemini, Claude, Perplexity, Meta Muse).

AGENT-TO-AGENT

Your Brand Agent Answers What A Personal AI Agent Asks

Shopper asks AI → Agent requests product information → Brand Agent sends a structured, enriched response via machine-readable protocols → Shopper gets a recommendation, answers and checkout.

AI agents (ChatGPT, Gemini, Claude, Meta Muse) interpret a shopper’s prompt and send a request to machine-readable protocols (ACP, UCP, JSON-LD, MCP). The Brand Agent draws on Product Context Memory and enables agents to recommend the right product.

MACHINE-READABLE

Thousands Of Product Descriptions, One Enriched Catalog, Every Format Agents Read

AI agents don’t browse like shoppers, they read structured data.
Your Brand Agent publishes your enriched catalog in every format they use:

AGENTIC COMMERCE PROTOCOL

ACP

The open standard for agent checkout that turns a recommendation into a purchase through checkout.

UNIVERSAL COMMERCE PROTOCOL

UCP

The open standard for shopping across merchants. Any agent can discover, cart and check out your products.

JSON FOR LINKED DATA

JSON-LD

Structured data embedded in product pages. It tells agents what a product is, what it costs and why it’s relevant.

MODEL CONTEXT PROTOCOL

Brand MCP

Agents query your product knowledge and live data directly, not what they last crawled.

JSON-LD

Go Beyond The ‘What’ With The ‘Why’ For Agents

Standard JSON-LD lists specs, price and stock. That tells an agent what a product is, not what it’s for.

Your Brand Agent generates enriched JSON-LD for every SKU from Product Context Memory, adding the needs, use cases and occasions that match how shoppers ask. It goes live on your brand PDPs, matched to the copy shoppers see, and the same enriched content syndicates to retailer PDPs through your existing PIM and commerce systems.

Standard JSON-LD output contains only product specs. Brand Agent’s JSON-LD is enriched via Product Context Memory and contains contextual descriptions that match the many ways in which shoppers actually ask AI.
GEO gets a brand named in text responses within LLMs. The Brand Agent enables products to be recommended with a link to buy.

GO BEYOND GEO

GEO Gets You Cited. 
A Machine-Readable Catalog Gets You Bought.

GEO publishes articles for LLMs to cite. That builds awareness, but it doesn’t sell products. AI platforms now build shopping on structured catalogs and they reward brand authority: enriched product data that comes straight from the brand, is accurate and stays current. Brand Agent delivers exactly that.

Frequently Asked Questions

How does a Brand Agent work?

The personal AI agent asks. The Brand Agent answers. A shopper’s agent requests product data through a standard protocol. Your Brand Agent responds with your enriched catalog, so the agent can match, choose and transact.

The open standards agents use to read and buy products. ACP and UCP cover catalog, cart and checkout. JSON-LD is structured data on your product pages. MCP lets agents query your product knowledge directly.

Any agent that reads these standards. That includes LLMs (ChatGPT, Gemini, Claude), personal AI agents (Meta Muse, OpenAI dots, Instinct) and retailer-owned shopping agents (Walmart’s Sparky, Amazon’s Alexa for Shopping). As new agents adopt the standards, your catalog is ready without being rebuilt.

A feed lists products. A Brand Agent represents them. Feeds carry specs, price and stock. The Agentic Discoverability Engine adds the context agents need and measures whether it sells. Brand Agent, the part of the engine that formats it, delivers your enriched catalog in machine-readable formats like ACP, UCP, JSON-LD and MCP, and keeps it current.

GEO can help build awareness. Brand Agent drives sales. Selling is shifting to agents. As ARK Invest puts it, “a merchant could be selling to an agent that is acting on the consumer’s behalf,” and “retailers risk irrelevance if they do not make their data accessible to agents.” Agents deciding what to buy rely on brand authority: structured, machine-readable product catalogs that come straight from the brand, enriched with the context shoppers use. That’s what your Brand Agent delivers.

Attributed discoverability, SKU by SKU. Product Discovery Insights shows which products agents recommend with a link to buy, and the lift after each cycle.

WONDERING ABOUT DISCOVERABILITY?

Stop Guessing.
Become Discoverable.

The Brand Agent is powered by the Agentic Discoverability Engine. It measures each product SKU’s gaps, contextually enriches it and delivers it to AI shopping agents in a continuous, always-on closed loop.