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Student Capstone Project 路 Spring 2026

AIr猫: Reimagining Fashion Through Intelligence

Buying the outfit is only one decision. AIr猫 helps users understand how a fashion item fits their wardrobe, lifestyle, and long-term ownership journey.

Student Team Andrea Penaloza and Barbara Herrera
Faculty Advisor Prof. Kirthi Kalyanam
Program Generative AI in Retail
Cohort Spring 2026
Andrea Penaloza and Barbara Herrera presenting the AIr猫 fashion intelligence project in a classroom

The Problem

Fashion decisions need more context.

Students shop for real moments: class presentations, internship interviews, dinners, club events, parties, and weekend trips. Yet the hard questions continue before and after checkout.

Will a piece work with what they already own? Can it be styled more than one way? Is it worth keeping, repairing, or eventually reselling?

The Solution

AI across the full fashion lifecycle

AIr猫 connects styling, virtual try-on, wardrobe intelligence, resale value, and repair guidance in one decision-support experience.

Virtual Try-On

Upload an avatar and clothing item to preview a potential look.

AI Wardrobe

Generate outfit ideas from the clothes the user already owns.

Luxury Resale

Estimate resale value and examine trends for higher-value items.

Repair Intelligence

Consider whether an item should be repaired, kept, or resold.

How AIr猫 Works

One platform for the life of every piece

The four capabilities are connected around the same ownership journey鈥攏ot added as isolated AI features.

Choose

Explore whether a piece fits the user's needs and personal style.

Try

Preview a clothing item with an uploaded avatar before deciding.

Style

Build outfits using pieces that are already in the wardrobe.

Use

Make each piece work across more moments and occasions.

Maintain

Consider repair before automatically replacing a damaged item.

Value

Understand resale potential when an item is no longer being used.

From Retail Assistants to Fashion Intelligence

The idea started with guided shopping.

Andrea and Barbara studied Amazon Rufus and Magic Apron by Home Depot, then carried conversational guidance into the fashion lifecycle.

The workshop explored how AI can improve customer decision-making throughout the shopping journey. The team saw an opportunity to move beyond finding more products and instead help customers understand how an item fits their wardrobe, lifestyle, and long-term plans.

AIr猫 combines retail intelligence with a visual identity inspired by Y2K websites, dress-up games, Clueless, futuristic fashion technology, and AWGE.

Why It Matters

Ask better questions than 鈥淲hat should I buy next?鈥

How can I style what I already have?
Does this item fit my wardrobe?
What might this piece be worth?
Should I repair, keep, or resell it?

Building Responsibly

Fashion AI is also a trust problem.

  • Virtual sizing and try-on results may be inaccurate.
  • Resale prices can change over time.
  • AI may not reliably authenticate luxury products.
  • Avatar and wardrobe uploads create privacy considerations.

With Gratitude

Thank you to Professor Kirthi Kalyanam

Andrea and Barbara thank Professor Kirthi Kalyanam and the Retail Management Institute at SA国际传媒 for creating a workshop where students could combine retail analysis, creative design, and responsible AI thinking.