EKOM is designed to connect wherever your product data lives.

• It can ingest data from Shopify and other ecommerce platforms, PIMs, feeds, and flat files.
• EKOM processes and optimizes that data, then writes back to your systems of record or export destinations (feeds, marketplaces, ad platforms).
• All of this runs within a SOC 2–certified, encrypted environment with role-based access controls.

You get a single optimization layer for product data—without replacing your existing stack.

EKOM doesn’t freeze at launch; it runs in continuous learning loops.

• It incorporates live performance signals (impressions, clicks, disapprovals, and search terms) where available.
• It updates rules and recommendations as platform requirements and shopper behavior change.
• New products inherit what’s already been learned from high-performing PDPs and feeds.

That means your catalog is always trending toward a healthier state, instead of drifting out of date.

EKOM runs anomaly detection across your catalog to find issues traditional checks miss.

• It looks for mismatched attributes (e.g., “cotton” in title, “polyester” in attributes).
• Flags missing or contradictory fields, like size charts, care instructions, or material details.
• Surfaces pattern breaks where one SKU deviates from how the rest of the family is structured.

Instead of manually hunting for errors, your team gets a prioritized queue of fixes mapped to specific products and fields.

EKOM combines semantic embeddings with natural language processing (NLP) to clean and optimize product data at scale.

• Embeddings are used to cluster related products, detect outliers, and map attributes to the language of search.
• NLP models then generate or refine titles, bullets, and descriptions so they stay consistent with your brand rules while matching the way customers search.

This gives you machine-readable product data that still feels natural and on-brand to humans.

When we say semantic, we mean EKOM understands the meaning behind your product data—not just the exact words.

• Product titles, attributes, and descriptions are mapped into vector embeddings (dense numeric representations of meaning).
• Those embeddings let EKOM connect SKUs to real search intent, even when shoppers phrase things differently across channels.

The result: your catalog is organized in a way that’s aligned with how humans and AI actually talk about products, not just how fields are labeled in your database.