StyleSync, the AI Wardrobe Assistant
StyleSync, the AI Wardrobe Assistant
My Team:
My Team:
Tools:
Tools:
Duration:
Duration:
2 Designers (Including Me)
2 Designers (Including Me)
Figma, FigJam
Figma, FigJam
March 2025
March 2025
CONTEXT
CONTEXT
Addressing a Market Gap
Addressing a Market Gap
StyleSync began as a response to a growing gap in the digital fashion space: while users often turn to platforms like Instagram and TikTok to share and discover outfits, there was no dedicated tool for planning and curating looks in a personalized, shareable way. I conceptualized StyleSync as an AI-powered outfit planner that allows users to upload, mix, match, and post outfits within one streamlined interface. The goal was to build a tool that not only made styling more intuitive and seamless, but also tapped into social behaviors—like event-based dressing and sharing looks with friends—through smart suggestions and customization.
StyleSync began as a response to a growing gap in the digital fashion space: while users often turn to platforms like Instagram and TikTok to share and discover outfits, there was no dedicated tool for planning and curating looks in a personalized, shareable way. I conceptualized StyleSync as an AI-powered outfit planner that allows users to upload, mix, match, and post outfits within one streamlined interface. The goal was to build a tool that not only made styling more intuitive and seamless, but also tapped into social behaviors—like event-based dressing and sharing looks with friends—through smart suggestions and customization.
RESEARCH
RESEARCH
Competitive Analysis
Competitive Analysis
We better understood this gap by conducting a brief, competitive analysis of platforms users currently rely on for outfit sharing and inspiration. While apps like Instagram, Reddit, and Snapchat offer community-driven advice, they all fell short on key features, and reinforced the need for a standard solution like StyleSync.
We better understood this gap by conducting a brief, competitive analysis of platforms users currently rely on for outfit sharing and inspiration. While apps like Instagram, Reddit, and Snapchat offer community-driven advice, they all fell short on key features, and reinforced the need for a standard solution like StyleSync.
PROCESS
PROCESS
Understanding Our Users
Understanding Our Users
The initial development process centered around on understanding the core problems users face in fashion and wardrobe management. We applied divergent and convergent thinking to explore a broad range of user pain points and through secondary research and user interviews, discovered five pain points of interest. Out of the five pain points we researched, we focused on addressing one in specific.
The initial development process centered around on understanding the core problems users face in fashion and wardrobe management. We applied divergent and convergent thinking to explore a broad range of user pain points and through secondary research and user interviews, discovered five pain points of interest. Out of the five pain points we researched, we focused on addressing one in specific.
Wasted Clothing
Up to 82% of clothing goes unworn each year in the average American’s wardrobe.
Wasted Clothing
Up to 82% of clothing goes unworn each year in the average American’s wardrobe.
Recognizing that a significant portion of wardrobes remains unused, we aimed to integrate a solution that encourages users to rediscover and utilize their existing clothing.
Recognizing that a significant portion of wardrobes remains unused, we aimed to integrate a solution that encourages users to rediscover and utilize their existing clothing.
Organizing by Mood/Style
Current platforms lack personalized styling options.
Organizing by Mood/Style
Current platforms lack personalized styling options.
Decision Fatigue
Outfit selection often becomes stressful when unsure.
Decision Fatigue
Outfit selection often becomes stressful when unsure.
Past Outfit Look-Up
There is no streamlined method for users to track previous outfit combos.
Past Outfit Look-Up
There is no streamlined method for users to track previous outfit combos.
Lack of Outfit Planning
Users rely on Instagram or Snapchat for outfit inspo, which don’t offer personal wardrobe management.
Lack of Outfit Planning
Users rely on Instagram or Snapchat for outfit inspo, which don’t offer personal wardrobe management.
PROCESS
PROCESS
Unique Proposition: Gamification
Unique Proposition: Gamification
How should we create a solution that’s unique and engaging?
How should we create a solution that’s unique and engaging?
Progress Bar Motivation
Progress Bar Motivation
Visual progress indicators give users a sense of momentum, encouraging them to continue decluttering until they hit completion.
Visual progress indicators give users a sense of momentum, encouraging them to continue decluttering until they hit completion.
Achievement Milestones
Achievement Milestones
Gamified checkpoints celebrate small wins along the way, rewarding users with playful feedback like 'Your clothes are clapping for you!'
Gamified checkpoints celebrate small wins along the way, rewarding users with playful feedback like 'Your clothes are clapping for you!'
Final Deliverable Presentation
REFLECTION
Journey as a UX/UI Lead
What I Would've Done Differently
In our initial MVP scope, we overestimated the number of features that we wanted to incorporate. This led to scattered priorities between me and Anshi and a longer timeline to validate core functionality. I would’ve rather, launched our interface faster, received more user feedback, and focused on more targeted iterations.
Challenges & Roadblocks
I scratched dozens of iterations before reaching our final product. While I originally sketched designs inspired by Cyberpunk, the reference they provided, I quickly learned surface-level research isn’t enough—deep contextual inquiry and continuous user feedback became essential for designing a product that caters to real-user behaviors.
Learnings
This was a special opportunity to mentor four other passionate designers. I facilitated team meetings twice a week, established and monitored individual and project milestones, and helped them learn complex Figma features, like auto-layout to ultimately prepare them to go on to become the next gen of design leads for GBCS.
What I Would've Done Differently
In our initial MVP scope, we overestimated the number of features that we wanted to incorporate. This led to scattered priorities between me and Anshi and a longer timeline to validate core functionality. I would’ve rather, launched our interface faster, received more user feedback, and focused on more targeted iterations.
Challenges & Roadblocks
I scratched dozens of iterations before reaching our final product. While I originally sketched designs inspired by Cyberpunk, the reference they provided, I quickly learned surface-level research isn’t enough—deep contextual inquiry and continuous user feedback became essential for designing a product that caters to real-user behaviors.
Learnings
This was a special opportunity to mentor four other passionate designers. I facilitated team meetings twice a week, established and monitored individual and project milestones, and helped them learn complex Figma features, like auto-layout to ultimately prepare them to go on to become the next gen of design leads for GBCS.
Connect with me!
junnlukas@gmail.com | LinkedIn
Final Deliverable Presentation
REFLECTION
Journey as a UX/UI Lead
What I Would've Done Differently
In our initial MVP scope, we overestimated the number of features that we wanted to incorporate. This led to scattered priorities between me and Anshi and a longer timeline to validate core functionality. I would’ve rather, launched our interface faster, received more user feedback, and focused on more targeted iterations.
Challenges & Roadblocks
I scratched dozens of iterations before reaching our final product. While I originally sketched designs inspired by Cyberpunk, the reference they provided, I quickly learned surface-level research isn’t enough—deep contextual inquiry and continuous user feedback became essential for designing a product that caters to real-user behaviors.
Learnings
This was a special opportunity to mentor four other passionate designers. I facilitated team meetings twice a week, established and monitored individual and project milestones, and helped them learn complex Figma features, like auto-layout to ultimately prepare them to go on to become the next gen of design leads for GBCS.
lukas junn
lukas junn
Connect with me!
junnlukas@gmail.com | LinkedIn
StyleSync, the AI Wardrobe Assistant
My Team:
Tools:
Duration:
2 Designers (Including Me)
Figma, FigJam
March 2025
CONTEXT
Addressing a Market Gap
StyleSync began as a response to a growing gap in the digital fashion space: while users often turn to platforms like Instagram and TikTok to share and discover outfits, there was no dedicated tool for planning and curating looks in a personalized, shareable way. I conceptualized StyleSync as an AI-powered outfit planner that allows users to upload, mix, match, and post outfits within one streamlined interface. The goal was to build a tool that not only made styling more intuitive and seamless, but also tapped into social behaviors—like event-based dressing and sharing looks with friends—through smart suggestions and customization.
RESEARCH
Competitive Analysis
We better understood this gap by conducting a brief, competitive analysis of platforms users currently rely on for outfit sharing and inspiration. While apps like Instagram, Reddit, and Snapchat offer community-driven advice, they all fell short on key features, and reinforced the need for a standard solution like StyleSync.
PROCESS
Understanding Our Users
The initial development process centered around on understanding the core problems users face in fashion and wardrobe management. We applied divergent and convergent thinking to explore a broad range of user pain points and through secondary research and user interviews, discovered five pain points of interest. Out of the five pain points we researched, we focused on addressing one in specific.
Wasted Clothing
Up to 82% of clothing goes unworn each year in the average American’s wardrobe.
Recognizing that a significant portion of wardrobes remains unused, we aimed to integrate a solution that encourages users to rediscover and utilize their existing clothing.
Organizing by Mood/Style
Current platforms lack personalized styling options.
Decision Fatigue
Outfit selection often becomes stressful when unsure.
Past Outfit Look-Up
There is no streamlined method for users to track previous outfit combos.
Lack of Outfit Planning
Users rely on Instagram or Snapchat for outfit inspo, which don’t offer personal wardrobe management.
PROCESS
Unique Proposition: Gamification
How should we create a solution that’s unique and engaging?
Progress Bar Motivation
Visual progress indicators give users a sense of momentum, encouraging them to continue decluttering until they hit completion.
Achievement Milestones
Gamified checkpoints celebrate small wins along the way, rewarding users with playful feedback like 'Your clothes are clapping for you!'
Final Deliverable Presentation
REFLECTION
Journey as a UX/UI Lead
What I Would've Done Differently
In our initial MVP scope, we overestimated the number of features that we wanted to incorporate. This led to scattered priorities between me and Anshi and a longer timeline to validate core functionality. I would’ve rather, launched our interface faster, received more user feedback, and focused on more targeted iterations.
Challenges & Roadblocks
I scratched dozens of iterations before reaching our final product. While I originally sketched designs inspired by Cyberpunk, the reference they provided, I quickly learned surface-level research isn’t enough—deep contextual inquiry and continuous user feedback became essential for designing a product that caters to real-user behaviors.
Learnings
This was a special opportunity to mentor four other passionate designers. I facilitated team meetings twice a week, established and monitored individual and project milestones, and helped them learn complex Figma features, like auto-layout to ultimately prepare them to go on to become the next gen of design leads for GBCS.
What I Would've Done Differently
In our initial MVP scope, we overestimated the number of features that we wanted to incorporate. This led to scattered priorities between me and Anshi and a longer timeline to validate core functionality. I would’ve rather, launched our interface faster, received more user feedback, and focused on more targeted iterations.
Challenges & Roadblocks
I scratched dozens of iterations before reaching our final product. While I originally sketched designs inspired by Cyberpunk, the reference they provided, I quickly learned surface-level research isn’t enough—deep contextual inquiry and continuous user feedback became essential for designing a product that caters to real-user behaviors.
Learnings
This was a special opportunity to mentor four other passionate designers. I facilitated team meetings twice a week, established and monitored individual and project milestones, and helped them learn complex Figma features, like auto-layout to ultimately prepare them to go on to become the next gen of design leads for GBCS.
Connect with me!
junnlukas@gmail.com | LinkedIn