Glenfield Adds looksy.tech AI Consultant: How a Personal Stylist and Virtual Try-On Work Together

The way customers navigate an online clothing store has barely changed in a decade: open the catalog, set filters, scroll through dozens of items. The tools around the catalog have improved — faster search, better photos, smarter recommendations — but the core experience remains the same: the customer does the work of figuring out what to buy.

AI is starting to change that. Instead of leaving shoppers alone with a grid of products, a store can now understand what someone is looking for and respond with a relevant, curated selection. One of the clearest examples so far is Glenfield, a major Russian fashion retailer that has deployed two looksy.tech AI services — and is seeing measurable results from the combination. The broader shift toward AI-driven personalization in fashion e-commerce is no longer theoretical; cases like this show what it looks like in practice.

What the looksy.tech AI Consultant Does

looksy.tech has launched a new product: an AI-powered consultant for online clothing stores. The service works as a personal stylist — it helps shoppers find items for a specific occasion and puts together complete outfits from the brand's current inventory.

Unlike standard “Frequently bought together” blocks, the AI consultant operates as a conversational interface. A customer describes what they need — “I'm looking for something for a business meeting” or “I need an outfit for a Friday night out” — and the service responds with specific products from the store's live catalog, available to purchase immediately.

This is a fundamentally different approach to catalog navigation. Instead of filtering by color, size, and price, the customer gets a curated selection that accounts for the context of their request. For fashion brands looking to choose the right AI tools for their store, this represents a new category of solution — one focused on discovery rather than visualization.

Why Glenfield: Context and Scale

One of the first brands to adopt the new service is Glenfield, a Russian fashion retailer with over 100 brick-and-mortar stores across the country. In parallel with its physical presence, Glenfield has been actively developing its online store and adopting digital tools to make online shopping easier and more intuitive.

The AI consultant is the second looksy.tech solution on Glenfield's website. Earlier, the brand integrated virtual try-on: customers upload their photo and see how a selected item looks on them. That deployment produced concrete results.

Virtual Try-On Results: Glenfield's Numbers

According to Glenfield's data, customers who used the virtual try-on feature:

• placed orders 1.5× more often than other site visitors;
• spent more time engaging with product cards;
• returned to items they had previously viewed;
• moved to checkout at a higher rate.

A 1.5× conversion lift is not an abstract benchmark — it is a real result on live traffic from a major retailer with over 100 locations. For a detailed framework on how to calculate virtual try-on ROI and payback period for your own store, we have covered the math in a separate article.

The conversion increase is driven by the same mechanism that makes physical fitting rooms effective: removing doubt. When a customer sees a garment on themselves rather than on a model, the gap between “interested” and “ready to buy” narrows sharply. This is well-documented in behavioral economics as the endowment effect — the tendency to value something more once you perceive it as yours. The psychology behind why virtual try-on converts is one of the strongest arguments for the technology.

How the Two Services Work Together

With both tools now live, the AI consultant and virtual try-on complement each other — forming a complete decision-support cycle:

This pairing addresses both key questions a shopper has: “What should I choose?” (consultant) and “How will it look on me?” (try-on). It is exactly the kind of personalized, interactive experience that Gen Z and Millennials now expect from online shopping.

Kirill Pegov, Co-Founder and CPO, looksy.tech

“For years, fashion retail has been actively developing online sales, but the process of choosing clothes has largely remained the same: the customer opens a catalog, applies filters, and compares dozens of items on their own. AI now allows us to change that scenario entirely. An online store can better understand what a person is looking for, help them choose, and offer a more personal experience. We believe this is the direction online fashion is heading, and the AI consultant is our next step in developing these services.”

This is consistent with a broader market trend: AI tools for fashion e-commerce are no longer experiments reserved for large corporations. Today, even small stores can deploy virtual try-on and compete with major marketplaces — the technology is available as a SaaS service with rapid onboarding.

Mikhail Kartashov, E-commerce Director, Glenfield

“Our experience with virtual try-on showed us that customers are willing to use new tools when they genuinely simplify the selection process. We saw a conversion increase among users of the service and realized we wanted to develop this direction further. Launching the AI consultant was a logical next step for us. Glenfield has a modern audience that actively engages with the brand online. It is important for us to continuously make this process simpler and more convenient and to offer customers useful new capabilities.”

What This Means for the Market

The Glenfield case matters not just for its numbers, but for its model. The brand sequentially adopted two AI tools, each solving a distinct problem — and the two reinforce each other:

• Virtual try-on lifts conversion on product pages, reduces returns, and increases time on site — which also improves the store's organic search rankings.
• The AI consultant solves the catalog navigation problem, deepens browsing, and drives cross-sell: the customer receives a complete outfit from multiple items rather than searching for each one individually.

For fashion brands already using virtual try-on, the AI consultant is a natural extension — it directs the customer to the right product, and the try-on helps them make the final decision.

For brands that have not yet adopted either AI service, the Glenfield case outlines a measurable path: start with virtual try-on, collect conversion data, then add the AI consultant for deeper personalization. See our guide to what to look for when choosing a virtual try-on provider — seven key criteria.