The Catalog Layer for Agentic Commerce

AI Is Already Buying From Your Competitors.

eLLMo is agent-to-agent infrastructure for the web of tomorrow: machine-readable catalogs, agentic pages and ads, and traced revenue. So AI can discover, cite, and transact with your brand. We don't monitor the problem. We fix it.

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Shopify · WooCommerce · WordPress · No replatforming required

For mid-market & enterprise DTC/CPG ($10M–$500M): same stack lowers wasted ad and content ops spend while lifting AI-attributed revenue and discoverability. U.S. retail traffic from generative AI tools surged 693% YoY in holiday 2025 (Adobe Analytics). Try interactive demos in-app after sign-in, or book a walkthrough.

Live Agent Activity
ChatGPTpurchasedVella Collective ×2·
PerplexityrecommendedLumière Skincare·
Perplexityskippedyour catalog·
Google AIrecommendedLumière Skincare·
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Google AIskippedyour catalog·
ChatGPTrecommendedVella Collective·
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PerplexityrecommendedLumière Skincare·
Perplexityskippedyour catalog·
Google AIrecommendedLumière Skincare·
ChatGPTskippedyour catalog·
PerplexitypurchasedLumière Skincare ×1·
Google AIskippedyour catalog·
ChatGPTrecommendedVella Collective·
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PerplexityrecommendedLumière Skincare·
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The problem

The Web Wasn't BuiltFor AI Agents

AI-driven retail traffic surged 693% YoY in holiday 2025 (Adobe Analytics). Yet most of it shows up as “direct” in your analytics. The channel is already here; it's just invisible.

When AI agents search for your products, they hit a wall. Your data lives in silos, images lack meaning, and the context agents need simply doesn't exist. Your brand stays invisible while competitors get cited.

Data Lives in Silos

Your inventory, product listings, brand voice, and policies are trapped across disconnected systems. AI agents can't piece together the full picture of what you offer.

No Semantic Structure

Traditional web pages are built for human eyes, not AI reasoning. Your product pages work beautifully for browsers, but agents can't extract the meaning they need.

Agents Cannot Complete the Journey

AI-powered surfaces can drive high-intent traffic, but agents often cannot find the right product data, answer questions with confidence, or complete a transaction. The result is dropped intent and lost revenue.

eLLMo AI fixes the catalog layer, making your product knowledge reachable, usable, and executable so discovery turns into engagement and checkout.

Same page — two realities

agent-request → yourstore.com/products/running-shoe

What a human sees

Product Image

All-Terrain Running Shoe

Lightweight · Waterproof · Sizes 6–13

$129.99

Add to Cart
Clear, engaging, converts well

What an AI agent encounters

GET /products/running-shoe-01

<img src="cdn/abc123.jpg" alt=""/>

⚠ alt text: empty

<div class="price">$129.99</div>

⚠ schema: missing

<div class="pdp-desc">...</div>

⚠ no structured attributes

⚠ cannot verify fit/material

⚠ no availability signal

→ RESULT: cannot recommend

Agent drops intent. Revenue lost.
AI agents are already crawling your catalog. Most are skipping it.

The shift is already happening

63%

Of sites in a 3,000-site sample received AI referral traffic

Ahrefs, 2025

693%

YoY growth in gen-AI traffic to U.S. retail sites (holiday 2025)

Adobe Analytics, Jan 2026

6-9 mo

First-mover window before catalog advantage compounds

eLLMo AI market view

“The brands that structure their catalog correctly today will own the AI recommendation layer for the next decade. This window is open for 6-9 months. After that, the gap compounds.”

Wins

Agentic Discovery
Drives Revenue

Shoppers increasingly research in generative AI before they buy. Retail referral traffic from those tools is growing triple digits year-over-year (Adobe). When agents recommend your brand, you win the session. When they don't, you may never know you lost it.

Invisible to agents. Then #1.

50,000+ daily visits, zero AI citation presence. Structured for agents across ChatGPT, Perplexity, and Google AI Mode.

#1
Top Answer Engine Recommendation
18%+
Clicks
80%+
Agentic Discovery Improvement

Full agent visibility. Zero replatforming.

10,000+ daily visits on a JavaScript-rendered site. Existing stack, no migration, full agentic discoverability unlocked.

Top 7
Highest Page Ranking in Preceding 12 months
82%+
Agentic Discovery Improvement
SPA (JavaScript)
No Replatforming Required

Outranked competitors in AI answers.

Competitors were being cited instead. Moved from unranked to #2 answer engine recommendation in category.

#2
Top Answer Engine Recommendation
60%+
Agentic Discovery Improvement

Your brand next.

Pilot one product category. Zero-engineering onboarding on Shopify, WooCommerce, or WordPress. First optimization in under 4 hours.

6-9 month window

Your competitor is already being cited. You may not know it yet.

Shoppers are discovering products through AI assistants and agents, not only your storefront. In a live walkthrough we connect the full arc: where demand and AI-driven traffic show up in Site Analytics, how you shape the experience in Experience Builder and Landing Pages, and how you prove what wins with A/B Testing. No setup required.

Show Me My Brand
Platform Architecture

Where Human and AI Journeys
Converge

eLLMo sits at the intersection of your brand's existing infrastructure and emerging AI discovery surfaces. We transform your website and product catalog into a unified, agent-ready knowledge layer that serves both human visitors and AI agents seamlessly.

Human and Non-Human Journeys Diagram showing how eLLMo connects brand infrastructure to AI agents and human visitors

URL Intelligence

Discover and evaluate URLs for AI citations, tracking reachability and semantic relevance across your entire site.

Learn more

Product Catalog

Enriched, structured product data served through standard protocols (UCP, ACP, MCP, A2A) for agent discovery.

Learn more

Content Intelligence

Multi-agent system that enriches product knowledge, generates semantic markup, and optimizes for AI understanding.

Learn more

Intent Intelligence

Routes queries to the right products, generates contextual product cards, and powers conversational commerce.

Learn more
Semantic Data Enrichment

See How We Transform
Product Pages

Agents can discover, compare, and check out when your PDP exposes complete, truthful structure. That means lower integration cost than duct-taping point tools, and higher revenue when agents can complete the journey.

BeforeAfter

Traditional PDP

Missing for Agents
Pro ANC Headphones
Best Seller4.8/5 (1,247 reviews)

Pro ANC Headphones

$129.99

Premium wireless headphones with active noise cancellation. Engineered for exceptional audio quality with 30-hour battery life. Perfect for professionals, commuters, and audiophiles.

Composition: Plastic housing, memory foam cushions, metal headband. Materials: ABS plastic, memory foam, aluminum.
Certifications: FCC, CE, Energy Star certified. Made in China. Recyclable packaging.
Care Instructions: Wipe with soft cloth. Store in provided case. Avoid moisture. Do not use while operating machinery.
Rich information exists, but it's unstructured and not machine-readable
What AI Sees
<div class="product">
  <h1>Headphones</h1>
  <span>$129.99</span>
  <p>Premium wireless headphones...</p>
  <div>Composition: Plastic housing...</div>
  <div>Certifications: FCC, CE...</div>
  <div>Care Instructions: Wipe...</div>
  // No structured data
  // Missing semantics
  // Incomplete entity
  // Can't extract use cases
  // Can't identify target audience
  // No canonical intents
}

Product detail page: agent view

What you see is a photo. What an agent sees is structure.

For agentic discovery and commerce, AI needs to find, match intent, and transact. Pick a product below and see how agent models encode the same image into nodes, attributes, and use-cases. That structure powers discovery and transaction on your PDP.

Wooden rack with denim jackets, knit sweaters, blouses, and jeans in neutral palette

Choose a product

Casual Neutrals Apparel Collection

One image. Four agent models. One unified representation so an agent can find and transact this product.

What the agent uses to match and transact (unified)

OBJECT: Apparel_Collection (curated ensemble)
ROLE: foundational_wardrobe_elements
CONTEXT: modern_casual_lifestyle
PRIORITY: versatility > aesthetic_cohesion > material_comfort > seasonal_adaptability
CONFIDENCE: high (multi-signal reinforcement from garment types, color harmony, and presentation style)

How agent models structure this product for discovery and transaction

Switch tabs to explore each model; no scrolling required.

Unified meta-representation

What an agent uses to match this product to buyer intent and complete discovery-to-transaction on the PDP.

OBJECT: Apparel_Collection (curated ensemble)
ROLE: foundational_wardrobe_elements
CONTEXT: modern_casual_lifestyle
PRIORITY: versatility > aesthetic_cohesion > material_comfort > seasonal_adaptability
CONFIDENCE: high (multi-signal reinforcement from garment types, color harmony, and presentation style)
Free agent audit

How does your product pageread to an AI agent?

Paste a product URL. We run it through five agent models and deliver a complete structured analysis straight to your inbox. No cost, no account required.

pdp-agent-report.json
OBJECT:   technical_shell_jacket
ROLE:     environmental_protection_layer
CONTEXT:  freshwater_angling

PRIORITY WEIGHTS:
  waterproofing    ████████████  0.94
  mobility         ████████░░░░  0.76
  storage          ██████░░░░░░  0.61
  aesthetics       ███░░░░░░░░░  0.28

AGENT SIGNALS:
  ✓ fishing_rod detected       (0.97)
  ✓ river_terrain context      (0.98)
  ✓ activity_inference: fly_fishing

OPTIMIZATION GAPS:
  ✗ structured_data missing
  ✗ material_composition unclear
  ✗ care_instructions absent

Graph and heatmap

How agents structure your product for discovery and ranking

Multi-model encoding

Vision, symbolic, semantic, and commerce models compared side by side

Optimization gaps

What is missing from your PDP for agentic visibility and transactions

We respect your privacy. No account required.

Vision modelSymbolic reasoningSemantic embeddingCommerce classificationUnified meta-representation
Zero-engineering onboarding

Up and running in under 4 hours.

Mid-market and enterprise DTC/CPG on Shopify, WooCommerce, or WordPress. No IT ticket. No replatforming. Same stack covers answer engines, AI shopping assistants, and paid: from impressions to citations to revenue you can trace.

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