“Layan” — AI shopping assistant
A conversational assistant, in Arabic, that guides customers through ordering directly from the storefront (“اطلبي مع ليان”).
Case study / Commerce & Creative
An Arabic-first fashion retail system where commerce, AI assistance, virtual try-on, and generative content operate as one connected product.

Independent fashion retail competes with global platforms on experience, content velocity, and service. Producing consistent campaign imagery for weekly drops, answering customers instantly, and helping shoppers trust how a garment will look — all of it traditionally demands teams that small brands don't have. The question behind YafaWear: can one connected system give a boutique brand that capability?
Arabic-speaking women shopping for occasion and everyday fashion — on mobile first — plus the store's own team operating merchandising, fulfillment, and customer conversations behind an Arabic dashboard.
Product architecture, full-stack build, and the AI workflow layer: defining the system design, building and iterating the storefront and its services with an AI-accelerated development toolchain, and connecting the commerce core to assistant, try-on, and generative content workflows. The production system runs on a dedicated repository connected to Cloud SQL and Google Cloud Storage.
A conversational assistant, in Arabic, that guides customers through ordering directly from the storefront (“اطلبي مع ليان”).
Customers can visualize garments before buying — the storefront's flagship AI feature.
Product suggestions driven by browsing and catalog signals across collections.
Campaign and collection visuals produced with controlled generative workflows to keep a consistent brand look across drops.
The system compresses what normally requires a content studio, a support team, and a development agency into one operable product: new drops go live with consistent visuals, customers get guided help at any hour, and the owner sees the whole operation in one Arabic dashboard. Qualitative outcomes are stated here deliberately — verified performance metrics will be published only when confirmed.
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