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Meet Aria — the AI model behind your commerce.

One domain-specific model working across try-on, diagnostics, personalization, basket building and loyalty, so every shopper interaction contributes to the next commercial decision.
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Aria connects the system.

Aria turns plain-language commercial goals into connected actions across the Experience Studio and the Agentic Hub's specialist agents. She works with customer, catalog, inventory and performance signals, so every recommendation reflects the wider business, not just the last prompt.

Illustration representing an ARview specialist commerce agent
Powers every capability
Aria routes each objective through the relevant experiences and agents while keeping context intact across the journey.
Illustration representing an ARview specialist commerce agent
Works with commercial context
Customer profiles, product availability, campaign priorities and performance signals inform every recommendation.
Illustration representing an ARview specialist commerce agent
Turns goals into executable plans
Describe the outcome. Aria recommends the right capabilities, audience, experience and next action.
Illustration representing an ARview specialist commerce agent
Aria
Managing 4 agents
Build a five-day routine campaign for our new SPF50 range, focused on high-intent younger skincare customers.
You
I power:
  • Skin Diagnostic Agent — identify the highest-fit profiles
  • Personalization Agent — define the relevant high-intent audience
  • Routine Agent — build the AM/PM sequence
  • Inventory check — confirm product availability before launch
Aria

Every specialist is built for one part of the journey.

Together, these eight specialists form the Agentic Hub. Activate the capabilities you need. Aria maintains the context between them, so discovery, recommendation and activation work as one connected system.

Illustration representing the ARview Try-On Agent
Illustration representing the ARview Try-On Agent

Virtual Try-On Agent

Photorealistic virtual try-on for makeup and accessories.
  • Real-time face tracking
  • Shade and finish exploration
  • Structured interaction signals
Typical outcome
Helps shoppers explore products and make choices with greater confidence.
Illustration representing the ARview Skin Diagnostic Agent
Illustration representing the ARview Skin Diagnostic Agent

Skin Diagnostic Agent

Camera-based analysis across 15+ skin signals from a single scan.
  • Individual skin profiles
  • Concern detection and severity
  • Product and routine mapping
Typical outcome
Turns diagnostic signals into relevant product and routine recommendations.
Illustration representing the ARview Routine Agent
Illustration representing the ARview Routine Agent

Routine Agent

Builds AM and PM routines around individual skin profiles, preferences and goals.
  • Product sequencing and layering
  • Goal-based routine progression
  • Replenishment timing
Typical outcome
Carries the recommendation beyond a single purchase into an ongoing routine.
Illustration representing the ARview Personalisation Agent
Illustration representing the ARview Personalisation Agent

Personalization Agent

Uses individual profile, behavior and product signals to make discovery more relevant.
  • Dynamic customer profiles
  • One-to-one product surfacing
  • Live audience and cohort updates
Typical outcome
Makes each interaction more relevant than the one before it.
Illustration representing the ARview Basket Builder Agent
Illustration representing the ARview Basket Builder Agent

Basket Builder Agent

Creates complementary bundles and intelligent cross-sell recommendations.
  • Product compatibility
  • Routine-aware bundles
  • Margin-conscious recommendations
Typical outcome
Builds more relevant baskets without relying on generic "customers also bought" logic.
Illustration representing the ARview Loyalty Agent
Illustration representing the ARview Loyalty Agent

Loyalty Agent

Manages replenishment, re-engagement and rewards around each customer's journey.
  • Lifecycle and replenishment triggers
  • Churn-risk signals
  • Tiered reward management
Typical outcome
Turns product discovery and purchase history into more relevant reasons to return.
Illustration representing the ARview Basket Builder Agent
Illustration representing the ARview Basket Builder Agent

Gift Agent

Helps shoppers find the right gift from your catalog, from one perfect product to a complete bundle.
  • Recipient and occasion matching
  • Budget-aware gift bundles
  • Swipe to Match discovery
Typical outcome
Turns seasonal gifting traffic into confident purchases.
Illustration representing the ARview Personalisation Agent
Illustration representing the ARview Personalisation Agent

Fragrance Finder Agent

Matches shoppers to fragrances by scent family, notes, mood and occasion.
  • Scent family and note profiling
  • Mood and occasion matching
  • Discovery sets and gift-ready picks
Typical outcome
Makes fragrance, the hardest beauty category to buy online, easier to choose.
New

Gift Agent for Christmas

A branded gift finder that helps shoppers choose the right gift from your catalog, by conversation or by swipe. Live within 2 weeks of payment.

Explore the Gift Agent
From commercial intent to connected action.
Icon representing color and undertone analysis
Icon representing color and undertone analysis

You set the objective

Describe the commercial outcome in plain language.
Icon representing personalized beauty profile creation
Icon representing personalized beauty profile creation

Aria selects the capabilities

She identifies the experiences, agents and context required.
Icon representing AI-curated product bundles
Icon representing AI-curated product bundles

The agents build the response

Diagnostics, recommendations, audiences and baskets contribute to one connected plan.
Icon representing confident purchase conversion after skin diagnostic scan
Icon representing confident purchase conversion after skin diagnostic scan

You review and activate

Your team remains in control of what is approved and launched.

Frequently Asked Questions

What is Aria?

Aria is ARview's domain-specific AI model for beauty and fashion commerce. She interprets commercial goals, works with customer, catalog, inventory and performance context, and powers the relevant experiences and specialist agents.

What do ARview's agents do?

ARview has eight specialist agents, each focused on one part of the shopper journey: virtual try-on, skin diagnostics, routine building, personalization, basket building, loyalty, gifting and fragrance finding. Aria connects their outputs so they operate as one system rather than separate tools.

Can we activate only the capabilities we need?

Yes. Brands and retailers can begin with a specific experience or use case, then activate additional agents as their requirements grow.

How long does implementation take?

Implementation depends on the selected experiences, catalog readiness and required integrations. ARview is designed to launch focused use cases first and add capabilities without rebuilding the entire customer experience.

What is ARview?

ARview is an agentic commerce platform for beauty and fashion brands and retailers. It combines skin diagnostics, virtual try-on, guided product discovery and personalized product matching with specialized commerce agents, all powered by Aria, ARview's domain-specific AI model for beauty and fashion commerce.

Read our practical guide to agentic commerce

Who is ARview for?

ARview is built for beauty and fashion brands, retailers and marketplaces. Brands can deploy experiences across websites, apps and physical retail environments, giving shoppers personalized ways to discover, evaluate and buy products while giving the business richer first-party data.

How is ARview different from a standard virtual try-on tool?

Most AR tools focus on visualization. ARview connects virtual try-on with diagnostics, product and catalog knowledge, guided discovery, personalization and specialized commerce agents. Every interaction can also contribute to a continuously learning commerce system, helping brands understand shopper needs, preferences and behavior rather than treating try-on as an isolated experience.

What data does ARview capture, and who owns it?

Diagnostic, try-on and discovery interactions can generate rich first-party data, including 15+ skin metrics, product preferences and behavioral signals. The data remains within the brand's environment and is not pooled or shared across competing brands. These signals can be used to improve personalization, product recommendations and understanding of shopper demand over time.