This document summarizes an AI assistant called MOS Studio that can help with various tasks in the fashion industry. It discusses how AI can improve efficiency and data-driven decision making. MOS Studio uses technologies like image generation, analysis, and recommendations to help with product management, market research, and other workflows. The business model involves subscriptions to access the tools for businesses, schools, and individuals. It aims to generate revenue and sees opportunities in the large AI market intelligence platform market. The founder and team have expertise in fashion, AI, and human-computer interaction and have published academic papers and patents related to fashion and AI.

1. Investor Relations
astyli
AI Assistant for Fashion
Business Support

2. How can AI be efficiently used at work?
Motivations

3. Motivations
Plan Design Development Sourcing
Distribution
Sales
Customer
service
management
Workflow for fashion MD
Continuous search, analysis, decision-making required
Product management life-cycle
Problem: lack of clarity in decision-making and efficiency of work, high dependence on qualitative experience

4. Motivations
Plan Design Development Sourcing
Distribution
Sales
Customer
service
management
Product Lifecycle Management (PLM)
PLM: Core application stage of digital transformation
pursued by fashion companies
Improving work efficiency, reducing time, and making decisions based on evidence,
such as identifying trends and responding to market demand

5. Business item
5
Business objectives
Speedy
Ideation
Rapid, evidence-based
decision making support
Digitalization &
Intelligence
Data and AI-based fashion
digital transformation support
User
Friendly
Easily accessible environment support
for data analysis
MOS Studio: AI Assistant for Fashion Business Support

6. Business item
6
Business item technology
Product
image
generation
Product
description
generation
Product
analysis
Product
recommendation/
sorting
MOS Studio
MOS
Analyzer
MOS
Generator
User requests (analysis, creation, search)

7. Business item technology
Fashion product information generation service
7

8. Business item technology
Product search and analysis service
8

9. Business item technology
Proof of concept (ongoing work with a major fashion
company)
9
Identification of AI technology needs that can support Fashion MD’s market research work
Need for similar products to be displayed when searching for desired products in market research
Our MOS technology can solve the process of ranking products similar to the desired product
Similarity-
based analysis
Expecting 20-30%
work efficiency
improvement

10. Business Model
10
Business Model
Revenue generation through MOS
Studio
MOS AI API service (SaaS)
B2B Service B2C Service
MOS AI solution to fashion companies
MOS Studio subscription service for
business
MOS Studio subscription service for
schools
Free MOS Studio for individuals (limited
services)
Subscription service for individuals (more
services)

11. Business Model
11
Business Model
Revenue
Stream
Beneficiary Payer Package Pricing
MOS Basic Free user Paid user
Unlimited number
of chat requests
1,000 image analysis
per month
Free
MOS Plus Paid user Paid user
Faster chat response times
5,000 image analysis
per month
24,000 won / month
MOS Business Customer employee Customer
MOS Plus
Customer data analysis
Image creation function
12,000 won / month
Revenue generation through MOS
Studio

12. Market size
12
Market size
$4T
$370M
$2.5M
SOM
MOS revenue
goal
SAM
AI-based market
intelligence platform
sector in Korea
TAM
AI-based market
intelligence platform
industry worldwide

13. Business Competency
13
Team members
Professor, Hanyang University, College of
Data Science
Scientist, US Pacific Northwest National
Laboratory
PhD, US Pennsylvania State University
AI, Data science, Human-Computer Interaction
expert
Kyungsik Han
PhD student, Hanyang University
Computer Engineering major
S/W development 3+ years
AI + Fashion research 2+ years
Taehyung Noh
Technology
development
PhD student, Hanyang
University
Computer Engineering major
S/W development 2+ years
AI + Fashion research 1+
year
Haein Yeo
Product manager
2023-2024
Marketin
g
1-2
people
Design
1-2 people
Recruitment
plan
Myungjin Kim
MS student, Hanyang
University
Fashion major
Fashion companies 3+
years
AI + Fashion research 1+
year
Product designer
Development
1-2 people
CEO

14. Business Competency
Technical expertise
A Study on User Perception and Experience Differences
in Recommendation Results by Domain Expertise: The
Case of Fashion Domains (Human Factors in Computing
Systems, 2023)
FashionQ: An AI-Driven Creativity Support Tool for
Facilitating Ideation in Fashion Design (Human Factors
in Computing Systems, 2021)
FANCY: Human-centered, Deep Learning-based Framework
for Fashion Style Analysis (The Web Conference, 2021)
ART (Attractive Recommendation Tailor): How the
Diversity of Product Recommendation Affects Customer
Purchase Preference in Fashion Industry? (Conference
on Information and Knowledge Management, 2020)
An Interactive Tool for Analyzing Fashion Style Trend
with Quantitative Criteria (Human Factors in Computing
Systems, 2020)
Better Targeting of Consumers: Modeling Multifactorial
Gender and Biological Sex from Instagram Posts
(Journal of User Modeling and User-Adapted Interaction,
Apparatus and method for classifying style based on deep
learning using fashion attribute
(Domestic Patent, 2022)
Apparatus and method for classifying user’s property
based on online data
(Domestic Patent, 2021)
Apparatus and method for predicting credibility of
online data
(Domestic Patent, 2020)
Fashion-AI related Patents
Academic Research Papers
(Fashion-AI research)
14

15. astyli
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