Occasion, silhouette, trend, cultural moment — these are the signals shoppers use when they search. For years, the infrastructure underneath fashion catalogs ignored all of it. Categories were flattened. Nuance was lost to automation. Teams compensated manually, endlessly, for tools that were never built with fashion in mind.
Perspiq was built to fix that structure. Not patch around it.
Our founding team brings over 20 years of experience building structured data systems and AI pipelines for production environments. We’ve seen what happens when intelligent technology meets real operational scale — and we know the difference between a working system and a demo that falls apart at 50,000 SKUs.
That experience is what Perspiq is built on. An application of structured data expertise to fashion retail’s most persistent and expensive problem.
We’re headquartered in Santa Clara, California.
Perspiq creates the intelligence layer between your product images and your commerce stack. Our models are trained on over 900,000 retail attributes from real fashion taxonomies — not generic internet images. They understand that “oversized” is a style intent, not a sizing error. That “quiet luxury” and “date night” are discovery signals, not decorative copy. That brand voice is a business requirement that doesn’t survive generic automation.
We surface uncertainty instead of hiding it. High-confidence outputs ship. Low-confidence outputs go to expert review before they reach your catalog. That’s the architecture — not a limitation of it.
We work with fashion retailers and brands that treat product understanding as a strategic capability. Teams that know bad catalog data isn’t an inconvenience — it’s a direct cost in abandoned searches, lost conversions, and manual hours that never end.
If discovery, search, and brand expression matter to your business, you’ll understand immediately why Perspiq exists.
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