Sartori is an AI-powered wardrobe intelligence platform that solves a core inefficiency in fashion: most recommendation systems treat clothing as isolated items rather than components of a complete wardrobe. Consumers struggle with purchase confidence, outfit coordination, and overbuying, while retailers face high return rates and low compatibility-driven conversion.
Sartori uses multimodal machine learning to model clothing at the wardrobe level, generating compatibility-based outfit recommendations instead of simple “similar item” suggestions. Today, we have a working beta with a live ML pipeline, structured catalog ingestion, embedding-based recommendation engine, and early user testing underway. We are refining performance metrics and preparing for scalable deployment and retail integration pilots.
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