THE PROBLEM

Your Catalog Was Built For Search, Not For Conversation.

Shoppers describe a need, an occasion, a problem. LLMs can’t match this to technical product descriptions. 

Different pain point-driven prompts from shoppers on AI platforms contrasted with factual product catalogs that don't match the prompts.

Nothing here matches what your shopper asked for.

Make Your Products Every LLM’s Recommendation

Marketers must now market to agents. The Agentic Discoverability Engine powers this by continuously:

  • Measuring where your products and links to buy don’t surface
  • Enriching them with the context shoppers actually use
  • Remembering it all in a product knowledge graph with Product Context Memory
  • Pushing it to LLMs in machine-readable formats – ACP, UCP, MCP, JSON-LD

This reinforces the brand authority that is critical for LLMs and stays constantly updated.

Product discoverability gaps identified, contextually enriched via reviews, social context etc., re-measured to prove lift

THE FIX

Product Context Memory: Describe A Product In Thousands Of Ways

One platform. Infinite context. Without thousands of landing pages.

Research agents contextually enrich product knowledge graph with reviews, social context; delivered across LLMs via MCP, JSON-LD, ACP, UCP
Dashboard showing product-level attributed discoverability gaps for ChatGPT, Gemini, Claude along with post-enrichment improvements.

PRODUCT DISCOVERY INSIGHTS

Close Sales Gaps With SKU-Level Attributed Discovery Measurement

Most measurement studies scratch the surface with broad brand-level insights. Product-level attributed discoverability and sales gaps remain unknown and enrichment is left to manual guesswork.

Product Discovery Insights shows you exactly where each product’s direct link to a sale is winning and losing on AI: across every major LLM, for key prompts, against competitors. It feeds into contextual product-level enrichment, then re-measures the lift via an MCP interface, so every improvement is proven, not assumed.

Test The Impact Of Enrichment For Each Product SKU In Minutes

Find the product context that gets each SKU discovered. Measure the lift across every LLM.

Closed loop measurement: identify product discoverability gaps for different prompts and A/B test discoverability post enrichment

THE VALUE COMPOUNDS

Enriched Product Descriptions Scaled Across PDPs: GEO+

Automatically generate machine-readable enriched product descriptions structured for both shoppers and agents. Deploy across brand and retailer PDPs that LLMs crawl, enhancing product discoverability, via:

  • PIM / PXM
  • PFM
  • JSON-LD
  • Brand MCP Service
  • Content Exports
GEO+ enhances product discoverability with contextually enriched brand and retailer PDPs made machine-readable for both humans and agents

THE SHIFT IS HERE

Your Product Catalog Measured, Enriched & Discoverable In Minutes

Launch the Agentic Discoverability Engine In Minutes. No Code, Human-in-the-Loop, Compliant.

STEP 1

Connect a product feed to get product-level insights

STEP 2

Agentic Discoverability Engine automatically runs for each product

STEP 3

Auto-generates LLM-compliant feeds: ACP+, UCP+, GEO+

WHAT COMES AFTER DISCOVERY?

Experience Takes ‘Discovered’ to ‘Chosen’

The Agentic BrandStore turns discovery into experience on AI platforms with your voice, your visuals, your recommendations, right inside the conversation, carrying the shopper all the way to purchase.