Catalog Enrichment
Your catalog already has the products. Catalog Enrichment gives the AI everything it needs to match them to the right customer. Connect your store once and the pipeline processes every product — tagging, relating, embedding — so recommendations are coherent from day one.
Style and use-case tags
Every product gets descriptive tags: material, style, colour, use-case, price tier, application context. These are the tags the customer's answers match against. The richer the tags, the sharper the recommendations. The AI does the tagging — you review and refine.
Compatibility mapping
The AI maps relationships between products. This plate pairs with these bowls. This glassware sits well on this table. The shortlist the customer sees is coherent — a curated set, not a list of individually similar items that don't work together.
Visual feature embeddings
Product images are processed into visual feature vectors. Style matching works because the AI understands aesthetics, not just labels. A customer who uploads a warm, earthy mood board gets recommendations that look the part — not just products tagged 'rustic'.
See Catalog Enrichment in action
Book a demo — we'll walk one product through the full enrichment pipeline.