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Galyra: AI Virtual Try-On
Agentic AI stylist and virtual try-on for Shopify fashion stores that styles each visitor, recommends outfits, and closes more sales.
Website, pricing, platforms and company facts side by side.
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| Website | open-gpt.app | iwand.style |
| Platforms | — | |
| Company | — | Startup from the United Arab Emirates · 1 - 9 employees |
| Listed in | — |
In their own words, as submitted to SaaSHub.


No description of https://open-gpt.app/ yet.
iWAND is a Shopify app that adds an AI stylist and virtual try-on to fashion stores. It runs eight agents: Style and Pair for outfit inspiration, Find and Snap for conversational and visual product search, and Consult, Complete, Refine and Size on the product page for fit questions, add-on...
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iWAND: AI Stylist & Try-On — Shopify App Demo
As answered by people managing https://open-gpt.app/ and iWAND.style.
iWAND.style's answer:
iWAND is a native Shopify app, distributed through the Shopify App Store and installed without code. It loads as a lightweight client-side widget and requires no theme-file modification.
It combines several AI capabilities: language models for the conversational agents, computer vision for visual search and wardrobe pairing, and generative image rendering for virtual try-on on matched models. It works across natural-language queries, shopper-uploaded images and the merchant's own product catalog.
It is delivered as a hosted service, so merchants install and configure it without running any infrastructure themselves.
iWAND.style's answer:
iWAND is a Shopify app that adds an AI stylist with virtual try-on to fashion stores. What separates it from other AI shopping tools is how much of the journey it covers and where it runs.
Most tools in this space do one job: virtual try-on, or size recommendation, or product search. iWAND runs eight specialised agents across the whole path to purchase — Style and Pair for outfit inspiration, Find and Snap for conversational and visual search, and Consult, Complete, Refine and Size on the product page. A merchant doesn't stack three apps to get one coherent experience.
It also runs inside the merchant's own storefront rather than as an external shopping agent. The assistant is fully white-labeled, speaks in the brand's voice, and 100% of first-party conversation data stays with the merchant.
iWAND.style's answer:
Shopify merchants selling fashion — apparel and accessories — where shoppers hesitate over fit, styling and how pieces work together.
It suits small and mid-sized independent fashion stores and DTC brands best. The free plan lets a boutique start without a budget conversation, and the eight agents supply the styling advice an in-store assistant would give but a product grid can't.
Native English and Arabic support makes it a particular fit for Gulf and wider MENA merchants, alongside stores in English-speaking markets.
It is not built for general merchandise, marketplaces, or non-Shopify platforms.
iWAND.style's answer:
Three reasons, and one reason not to.
Coverage. Most alternatives handle one stage — try-on, or sizing, or search. iWAND covers inspiration, discovery and the product page with eight agents in a single install.
The brand stays the merchant's. External AI shopping agents flatten the brand and keep customer conversation data in a black box. iWAND runs inside the merchant's store, fully white-labeled and speaking in the merchant's voice, and leaves all first-party conversation data with the merchant.
No development work. Installation requires no code and no theme-file modification. iWAND loads as a lightweight widget, so a store owner can run it without a developer or an agency.
Where iWAND is not the right choice: stores on WooCommerce, Magento or any non-Shopify platform; catalogs outside apparel and accessories.
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