Case Study · Social Impact · AI Product

AdaptAI

Fashion has always had a size problem — but for people with disabilities, it goes far deeper. AdaptAI uses AI to design beautiful, adaptive clothing that works with every body, not against it. Built at Cornell University, this is product management in service of dignity.

Role
Founder & Researcher
Context
Cornell University
Timeline
Aug 2025 – May 2026
Tools
VLMs · Python · Figma
Visit live app ↗
100+
Students Supported
40%
Cost Reduction
28–35%
Artisan Income Growth
30+
Brand Studies Conducted
C
Comprehend the Situation

What problem really exists here?

The global adaptive fashion market is nearly invisible. Over 1 billion people with disabilities are routinely excluded from mainstream fashion. Standard clothing ignores wheelchair users, people with sensory sensitivities, limited dexterity, and unique body shapes. The 'accessible' options that exist are clinical, expensive, and strip people of their identity.

At Cornell's Student Disability Services, I saw this firsthand. Students who needed adaptive clothing either couldn't find it, couldn't afford it, or were forced to wear something that made them feel less — not more — like themselves.

What

An AI-powered platform that generates personalized adaptive outfit designs with hidden accessibility features — magnetic closures, side openings, seated silhouettes — built into beautiful, trendy looks.

Why

Fashion is a form of self-expression and dignity. Excluding people with disabilities is not just a product gap — it is a social justice issue. The goal: eliminate the barrier between disability and style.

Who

Cornell students with disabilities (100+ served through SDS), wheelchair users, people with sensory sensitivities, mobility-impaired individuals, and the artisans who serve them.

How we measure success

Users served · Reduction in garment cost · Artisan income growth · User confidence scores from interviews · Design adoption rate through Cornell's SDS program.

I
Identify the Customer

Who are we truly building for?

Through 10+ deep-dive interviews and 30+ brand studies, two distinct user groups emerged — each with urgent, unmet needs that mainstream fashion completely ignores.

Primary User

The Person With a Disability

Students, young adults, and individuals with physical disabilities, mobility challenges, or sensory sensitivities who want to feel stylish — not just functional.

Needs
  • ·Clothing that works with their mobility aid or body type
  • ·Adaptive features that are invisible — not clinical
  • ·Affordable options (bespoke adaptive clothing was $300–500+)
  • ·To feel confident, stylish, and seen by fashion
Secondary User

The Artisan & Small-Scale Maker

Independent tailors, fashion makers, and small studios who want to serve the adaptive market but lack the pattern expertise and tools to do so affordably.

Needs
  • ·Accessible adaptive pattern templates
  • ·Reduced design iteration time
  • ·A new, underserved revenue stream
  • ·AI tools that don't require deep technical expertise
R+C
Report Needs & Prioritize

What hurts most — and why it matters

From 10+ user interviews and surveys through Cornell's SDS program, pain points were mapped across urgency, frequency, and impact.

Pain pointUrgencyFrequencyImpactChosen
High cost of adaptive clothingHighHighHigh
No stylish options, only clinicalMedHighHigh
Poor fit for mobility aidsHighHighMed
Lack of awareness / discoveryMedMedMed
"Cost and style are the two biggest barriers to entry. If we solve those, everything else becomes possible. An adaptive outfit that's affordable and beautiful changes how someone moves through the world."
L+E
List Solutions & Evaluate

Three solutions. One direction.

Solution 01

AI Outfit Generator

User inputs their mobility needs, body shape, style preferences, and favorite colors. AI generates a complete adaptive outfit design with hidden accessibility features built in — and an image prompt to visualize it.

Solution 02

VLM-Powered Pattern Generation

Using Vision Language Models and Python analytics pipelines to auto-generate adaptive sewing patterns — reducing the cost and expertise barrier for independent makers and artisans.

Solution 03

Curated Gallery of Adaptive Designs

A browsable gallery of AI-generated adaptive looks — low-friction discovery for users who want inspiration before committing to a custom design session.

Tradeoffs
SolutionProCon
AI Outfit GeneratorScalable, deeply personalized, immediate valueRequires AI API cost management
VLM Pattern GenerationReduces artisan cost by 40%, enables supply chainComplex; requires Python pipeline
Curated GalleryLow friction, fast to build, high engagementLess personalized; passive experience
Final Decision

"Launch AI Outfit Generator + Gallery together as the user-facing product. Use the VLM pattern pipeline in the backend to power the artisan supply chain — creating value on both sides of the market simultaneously."

S
Summarize & Impact

What we built. What we changed.

AdaptAI shipped as a live web app with a Design Studio, Gallery, and full AI-powered outfit generation. But the numbers only tell part of the story. The real impact is in the students who finally felt seen by fashion.

  • 100+ Cornell students with disabilities supported through SDS
  • 40% reduction in per-garment cost via AI-generated patterns
  • 28–35% projected artisan income growth via Cornell's Inclusive AI Supply Chain research model
  • 30+ brand studies conducted across adaptive and luxury fashion
Social Impact

"AdaptAI is not a fashion app. It's a statement that disability is not a design constraint — it's a design opportunity. Every person deserves to feel beautiful, confident, and seen. AI, used with empathy and intention, can finally make that possible at scale."