Intelligence

The AI that understands bodies, not just keywords

StyleMind's intelligence layer combines a 3D body model, semantic understanding, and a real-time fit engine to recommend what actually fits — every time.

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User Memory

StyleMind remembers every shopper across sessions — their preferences, past interactions, sizes, and style choices. Every visit picks up exactly where the last one left off.

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Semantic Style Engine

Understands natural language the way humans do. When a shopper says "rooftop party," StyleMind doesn't just search for "dress" — it infers occasion, formality, silhouette, and fabric weight simultaneously.

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Real-time Fit Scoring

Every recommendation is scored against the shopper's style profile and preferences before it's surfaced. Our model achieves 97% accuracy on the first recommendation, reducing decision fatigue and returns.

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Continuous Learning

The model improves with every sale, return, and session — across all StyleMind merchants. A return at one store makes recommendations smarter for shoppers at every store.

How it works

From first visit to confirmed sale in under 200ms

01
Shopper arrives
Agent detects entry and begins passive signal reading
02
Agent reads signals
Device type, browsing history, click patterns, and explicit inputs are collected
03
Style profile built
Preferences and style choices are retrieved from memory or collected through a conversational flow
04
Fit scored
Every matching item in your catalog is ranked by fit, style match, and inventory
05
Sale closed
Shopper receives a curated recommendation with confidence — and buys
97%
fit accuracy
<200ms
response time
40M+
items indexed
3×
avg conversion lift

Frequently asked questions

Everything you need to know about StyleMind's intelligence engine.

How does StyleMind's user memory work?+

StyleMind remembers each shopper's preferences, style choices, and past interactions across sessions. This persistent user memory is used to personalise every recommendation, so returning shoppers get better results every visit.

What is the Semantic Style Engine?+

The Semantic Style Engine interprets natural language shopping intent beyond keywords. When a shopper says 'rooftop party outfit,' StyleMind infers occasion, formality level, silhouette preference, and fabric weight simultaneously — returning contextually relevant results rather than keyword matches.

How fast does StyleMind respond?+

StyleMind's intelligence layer delivers recommendations in under 200 milliseconds, scoring every item in the catalog against the shopper's style profile in real time.

How many products can StyleMind index?+

StyleMind indexes 40M+ items across its merchant network. Each merchant's catalog is synced automatically and updated in real time as inventory changes.

Does StyleMind improve over time?+

Yes. StyleMind uses continuous learning across all merchant deployments — every sale, return, and session makes the fit model more accurate for all stores.