The Problem

70% clothing returns

in e-commerce globally are due to poor fit

across brands, leading to consumer confusion.

No global sizing standard

Bracketing

...shoppers frequently order multiple sizes, returning most

in return costs and logistics inefficiencies

$100B+ lost annually

Higher return rates contribute to increased carbon emissions and waste

Environmental Impact

The Solution <fitfyn>

AI-powered universal sizing recommendations across all brands.

Users input their size in one brand and get accurate fits across multiple brands.

"Powered by FitFyn" Toggle API allows retailers to enable seamless size filtering.

Cross-platform compatibility for integration with e-commerce platforms.

Sustainability Impact: Reduces returns, lowering carbon emissions and textile waste.

How it Works

01. User Input→

Enters Known size or body measurements

02. Data Mapping→

03. AI Processing→

04. Output→

05. Feedback loop →

FitFyn compares against brand specific charts

Predicts best fit based on user history, fabric stretch & regional differences

User receives accurate, cross-brand size recommendation

AI refines predictions based on user feedback

Market Sizing

Addressable Market

Global Online Fashion Market: $500B+

Annual Apparel Returns: $100B+ (40% due to sizing issues)

Retailers’ Pain Point: 40% of returns come from fit-related issues.

E-commerce brands & marketplaces struggling with returns

Consumers frustrated by inconsistent sizing

Sustainable fashion brands aiming to reduce returns and waste

Business Model

01. B2C

Freemium Model: Basic size recommendations are free; premium AI fit analysis at $4.99/month.

Affiliate Commissions: 3-10% per transaction from partnered retailers.

02. B2C

API Subscription Model: Retailers pay $5K-$50K/month for AI sizing integration.

03. B2B

04. B2B

Return Reduction Guarantee: Performance-based fees for reducing return rates.

"Powered by FitFyn" Toggle API: Retailers allow customers to filter for perfect-fitting products.

05. B2B

Competitive Advantage

True Fit

Limited to partnered retailers; <FitFyn> provides cross-brand sizing standardization.

Works within select retailers; FitFyn aggregates all brand size charts.

Fit Finder

Manually entered and inaccurate; FitFyn uses AI-driven recommendations.

Generic Size Charts

FitFyn’s ML model will be uniquely trained to map and compare brand-specific sizing across retailers, creating an unmatched data advantage

Proprietary AI Algorithms →

Exclusive Data Aggregation →

FitFyn aims to build a comprehensive, structured sizing database that does not currently exist elsewhere, establishing a strong data-driven moat.

Key Features/ Differentiators

As FitFyn gains more users and brand partnerships, the AI model will continuously improve, making it increasingly difficult for competitors to replicate the accuracy and personalization.

FitFyn plans to offer the 'Powered by FitFyn' toggle API, embedding directly into retailer websites to create deep partnerships and ensure long-term adoption.

Network Effects & AI Learning →

API-Driven Retailer Integration →

Sustainability Differentiation →

FitFyn aims to position itself as a solution for both consumer convenience and environmental impact reduction, aligning with retailer sustainability goals.

Barriers to Entry

Data Complexity & Proprietary Dataset →

FitFyn will need to collect, standardize, and maintain a global sizing database across brands, requiring extensive infrastructure and partnerships.

AI Training &
Accuracy →

FitFyn will require years of machine learning refinement to achieve a high level of precision in size recommendations.

FitFyn plans to secure early API adoption by retailers, creating high switching costs and making it difficult for competitors to displace us.

Retailer Partnerships & API Lock-in →

FitFyn will need to establish credibility in the fashion-tech space, ensuring strong early traction to create a first-mover advantage.

Brand Trust &
User Adoption →

FitFyn will need to navigate complex consumer data protection laws and establish best practices for compliance in global markets.

Regulatory Compliance & Data Privacy →

A seasoned entrepreneur and product strategist with deep experience in scaling tech-driven startups. Kimmy has worked extensively in consumer experience, business growth, and AI-driven solutions, making her instrumental in positioning FitFyn as a game-changing solution in fashion-tech.

Team <FitFyn>

A design and product strategy expert with experience in user experience, AI personalization, and global market scaling. Vivek has successfully led consumer-facing digital products and is passionate about creating intuitive, AI-powered solutions for e-commerce

Kimmy Nagpal (Co-founder)

Vivek Juyal (Co-founder)

We strongly believe that the strength of a startup lies in its team. At FitFyn, we are aiming to assembling a world-class team that blends expertise in AI, fashion-tech, and e-commerce. Our success will be driven by the talent, passion, and dedication of our people, ensuring we execute on our vision and build a product that transforms the industry.

Contact Us

We are always looking to connect with those who share our vision. Whether you're a potential partner, investor, or someone who wants to contribute to this mission, we'd love to hear from you.

📩 Leave us a message, and we’ll get back to you as soon as possible.
Let's redefine how the world shops for fashion—together. 🚀