AI Catalog Optimization
We make product catalogs
perfectly understandable
to AI.
AI search engines need clear product meaning, consistent attributes, and structured schemas. Most catalogs weren't built for that. EKOM fixes it.
Overall Readiness
0
/100Recommendation: Image alt text is the highest-impact gap. Improving coverage could raise your score by 12 points.
Most catalogs were built for humans.
Not AI.
AI search engines and LLMs need clear product meaning, consistent attributes, structured schemas, and entity clarity. Most catalogs have short marketing copy, half-missing attributes, incomplete schema, and vague product types. AI systems struggle to understand that.
Four dimensions of
AI understanding.
Every improvement EKOM makes passes one test: does this help AI systems understand the product better?
Product Meaning
Titles, descriptions, product type, and taxonomy. These help AI understand what the product is.
Semantic Attributes
Material, color, compatibility, audience, and use case. These help AI understand what the product is for.
Structured Schema
Schema.org product markup, OpenGraph, and AI crawler signals. These help AI parse the product correctly.
Entity Clarity
Brand, variant logic, and product grouping. These help AI understand relationships between products.
Scan. Fix. Deploy. Repeat.
A continuous loop that takes your catalog from incomplete to fully ready. No spreadsheets, no agencies, no months of work.
Scan catalog
Ingest and analyze your entire product catalog
Detect gaps
Find what AI systems can't understand
Generate fixes
Structured improvements, not guesswork
Review patches
Your team approves every change
Deploy
Push improvements to your store
Rescan
Continuous improvement loop
One score tells you
how AI sees your catalog.
The AI Understanding Score measures product meaning, semantic attributes, structured schema, and entity clarity. Watch it climb as you approve fixes.
Fixes available
Your titles are too short for AI systems to understand the product context. I can expand them with material and product type.
Most products are missing material attributes. AI systems use this heavily for comparisons and recommendations.
Your schema markup is incomplete. Adding it will help AI crawlers interpret your catalog correctly.
Your agent teaches you
how AI sees your catalog.
Not a chatbot. Not a dashboard. An intelligent agent that understands your catalog semantically and explains exactly what AI systems need to recommend your products.
We're not a PIM.
We make your products understandable to AI.
We don't manage price, inventory, SKU logic, GTIN workflows, supplier data, or warehouse data. If those are wrong, we flag them \u2014 but the fix happens at the source. EKOM stays laser-focused on AI catalog optimization.
Invisible products used to be inevitable.
Now, AI-ready data takes minutes.
AI search engines demand structured, complete product data. EKOM's agent ensures every listing is semantically clear, structurally complete, and AI-ready.
- Spreadsheets passed between teams
- Months to update a catalog
- Agencies for basic data entry
- Products invisible across channels — and no one knows why
- Agent scans your catalog against AI standards
- Semantic gaps detected and fixes generated
- Nothing changes until you approve
- AI Understanding Score climbs with every session
No rip & replace.
Connect your store and your agent starts working. No migration, no dev resources, no disruption.
Common questions
AI Catalog Optimization
You are not managing product data.
You are teaching AI how to understand it.
That is a much sharper mission. And EKOM is the platform built for it.