for fashion
make fashion shoppable by ai
fashion is the hardest catalog to make ai-legible, and the biggest opportunity. alana scores, enriches, generates looks, powers style-aware search, and distributes across every ai surface.
the fashion challenge
fashion catalogs are uniquely hard for ai
rich, messy attributes
fabric, fit, silhouette, occasion, season: fashion data is deep and inconsistent, and ai can’t recommend what it can’t parse.
style is visual & contextual
“something elegant for a summer wedding” isn’t a keyword. ai has to understand aesthetic, occasion, and vibe.
fast, seasonal turnover
collections change constantly. your ai readiness has to keep up automatically, not with a quarterly project.
media does the selling
on-model shots and full looks convert. thin, single-image SKUs are invisible to both shoppers and ai.
the fashion stack
everything a fashion catalog needs to be ai-ready
score · channel 1
style-aware ai commerce score
see how ai reads every SKU (attributes, media richness, and style context) with prioritized fixes for the pieces dragging you down.
- fabric, fit, occasion, and silhouette completeness
- media richness scored per product
- style and aesthetic context, not just keywords
ai commerce score
ai-ready+14 this month
aurora silk midi dressai-ready92
merino wool overcoatgood78
canvas low-top sneakerneeds work54canvas · media
generate looks & on-model media
turn flat product shots into full looks, on-model imagery, and in-scene media: the assets that actually sell fashion, generated from your catalog.
- compose complete looks from individual SKUs
- on-model and in-scene generation (e.g. “parisian café”)
- style tags for search, assistants, and merchandising
canvas · media
aurora silk midi dress
catalog
ai-generated
ai-composedassistant · channel 2
a style assistant on your storefront
let shoppers describe what they want (occasion, budget, vibe) and get complete, buyable looks. conversational shopping powered by your enriched catalog.
- understands occasion, fit, budget, and aesthetic
- recommends complete looks, not just single items
- refines by follow-up (“more formal”, “in blue”)
search · channel 2
search that understands style
replace keyword search with intent understanding. “something elegant for a summer wedding” returns the right pieces, never a zero-result page.
- natural-language, style, and occasion understanding
- visual & similar-item search
- drop-in for vtex, shopify, and headless storefronts
ai search · your storefront
understood intent · no zero results · 3 matches
aurora silk midi dress
silk · evening · sapphire
merino wool overcoat
wool · winter · tailored
leather crossbody bag
leather · everyday · compact
keyword vs ai
same query. one understands it.
legacy search matches words. alana understands the shopper, and returns a complete, buyable look.
case study
“a leading latin american fashion marketplace runs alana on top of vtex, enriching thousands of SKUs, generating look compositions, and powering a conversational style assistant that turns browsing into assisted revenue.”
fashion marketplace · latam · on vtex
thousands
of SKUs enriched
looks
generated from the catalog
assisted
revenue as the north star
runs inside vtex. no re-platforming. connect your catalog as-is.
ready to make your catalog shoppable by ai?
start with a free ai commerce score and see exactly how ai assistants see your products.