Missing colors, unlabeled materials, and inconsistent titles hurt search conversion. NexorAIQ AI Catalog Enrichment analyzes titles, descriptions, and images to automatically generate structured attributes and facets.
How multimodal models extract attributes, normalize units, and enrich catalogs without manual data entry.
NexorAIQ ingests your existing catalog via Magento 2, Adobe Commerce or CSV (more connectors coming soon) without requiring complex schema changes.
Our commerce models analyze product descriptions, specifications, and photography to identify missing merchant attributes.
Extracted tags are mapped to clean, uniform categories and instantly populate dynamic search filters and search relevance.
Enrich thousands of raw SKUs per hour with high-converting tags, filters, and standardized taxonomy.
Detects exact shades (e.g. 'sage green', 'burgundy') directly from product photography even if not written in copy.
Extracts composition percentages (e.g. '98% Cotton, 2% Elastane') into structured filterable attributes.
Standardizes inches to centimeters, ounces to grams, and resolves confusing sizing notations automatically.
Applies high-intent lifestyle tags like 'Cocktail Party', 'Black Tie', 'Minimalist', or 'Summer Resort'.
Enrichment runs securely in the cloud search index; your live commerce store remains fast and completely untouched.
Review high-confidence tags automatically while flagging edge cases for merchant review in the dashboard.
See how marketplaces and high-SKU retailers eliminate empty facet filters.
Standardize messy third-party vendor listings into clean, uniform faceted navigation filters.
Extract heel heights, toe shapes, closure types, and lining materials across thousands of footwear SKUs.
Extract pipe diameters, thread types, finish coatings, and compatibility ratings from product spec sheets.
Tag dietary requirements: Gluten-Free, Non-GMO, Vegan, Keto, Kosher, and Halal with 100% compliance tracking.
Everything you need to know about Catalog Enrichment and how it drives e-commerce revenue.
It reads product titles, descriptions, specs and images and generates structured attributes such as color, material and fabric composition, and occasion or style tags, which then become search filters.