Product & Content Designer
StyleMorph
Role: Product Designer, UX Researcher
Team: Software Engineer, Product Manager
Basic Process: Research > Ideate > Design > Prototype > Iterate
Timeline: Two weeks
Tools: Figma, Adobe Illustrator, HuggingFace, Keynote
Overview
StyleMorph is an innovative platform that empowers fashion designers by transforming text prompts and sketches into stunning design concepts. This project harnesses the power of AI to generate personalized fashion trends and prototypes, incorporating user preferences for styles, colors, and patterns while promoting inclusivity through customizable model diversity.
With its seamless, user-friendly interface and advanced customization features, StyleMorph reimagines the creative process, acting as an intuitive design assistant that amplifies human creativity while making fashion design more accessible for all.
CHALLENGE
With the rise of AI-powered creative tools, designers face questions around authorship, originality, and collaboration.
This project given to us at the Institute of Design, Illinois Institute of Technology challenged us to explore how AI can support creativity while fostering inclusivity and color accessibility. Our task was to select an AI model, research its data sources, and design an interaction that enhances creative workflows. The goal was to empower creators by integrating transparent, adaptable AI interactions that evolve with user needs.
RESEARCH
Competitive Analysis
My research focused on how these platforms approach the following key aspects:
Collaboration Tools
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How do they facilitate interactions between creators and AI?
Transparency and Adaptability
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How do they communicate AI processes and outputs to users?
Accessibility
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How do they handle color accessibility and inclusivity for diverse users?
Key findings included
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Many tools prioritize output generation but often lack transparency about how AI decisions are made.
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Some platforms succeed in collaboration features but struggle to make interfaces accessible, especially in terms of color contrast and customizable controls for diverse users.
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Few tools offered integrated cross-device experiences where mobile and desktop workflows felt unified and complementary.
Data Source Exploration
To better understand the ethical and functional aspects of our chosen AI model, I researched the data sources feeding the AI’s training.
This included analyzing:
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The diversity and representation within the datasets.
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Potential biases that could impact creative outputs.
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The need for transparency in how the model adapts to different user behaviors and requests.
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This step was crucial in designing interactions that empower creators by providing insight into how the AI arrives at recommendations while giving users control to adjust and customize outputs.
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User Needs
Based on the research, I identified key user needs:
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Creative Freedom: Creative professionals seek interfaces that support their unique workflows and foster innovation.
Inclusivity: The tool must accommodate diverse users by offering customization options, such as accessible color palettes and the ability to adjust race and body type for generated AI models.
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These insights shaped our decision to develop both mobile and desktop solutions aimed at delivering a seamless, inclusive experience across platforms.
USER FLOW
I sketched out potential user flows and interaction patterns, focusing on ways to foster inclusivity and creative freedom in the interface. I explored various ideas for layout, customization options, and accessibility features, prioritizing simplicity and seamless collaboration between users and the AI system. .
DESIGN
Visual Architecture
I chose the Outfit typeface for its clean, modern style and excellent legibility across devices, ensuring accessibility for users of varying needs.
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The color palette was chosen with inclusivity in mind, prioritizing accessibility for individuals with common visual impairments, such as color blindness.
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The orange and navy hues provide strong contrast, while the white and lavender tones balance the interface, making it visually engaging without overwhelming the user.
This combination supports a sleek and intuitive user experience, reinforcing StyleMorph’s commitment to inclusive and creative fashion design.
Onboarding
In the onboarding flow, I introduced core features like AI-powered design visualization, diverse model selection, and text-to-image transformation, so new users grasp the app’s value at a glance. By balancing concise microcopy, bold imagery, and progressive disclosure, the design minimizes cognitive load and boosts engagement. A simple, streamlined signup further reduces friction, making it easy for users to dive in and start creating.
Library
The Library offers a streamlined space for users to store, access, and manage designs effortlessly. With sorting, filtering, and categorization, I designed an intuitive layout that makes finding saved outfits, sketches, and inspirations quick and easy. A clean grid and distinct previews enhance navigation for a seamless experience.
AI Models
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With AI, users are able to select preferences on fabric types, color palettes, and model variations, emphasizing StyleMorph’s commitment to inclusivity and creative freedom.
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Community
The Community section fosters collaboration by allowing users to share designs, exchange feedback, and engage in discussions. I designed it as a social yet professional space, integrating likes, comments, sharing, and profile customization to encourage creative exchange while keeping the experience intuitive and user-friendly.
FUTURE ITERATIONS
To improve the current design I have found two areas of focus.
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Enhanced Collaboration Tools: Adding a feature where users can share their work-in-progress designs within the app and receive real-time feedback from collaborators.
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Dynamic Trend Recommendations: Implementing real-time updates that suggest trending fashion elements based on current industry patterns could elevate user experience.
REFLECTION
​The StyleMorph project was praised for its innovative approach to using AI in fashion design.
We received positive feedback particularly about the intuitive user flow, inclusive customization features, and clean, accessible interface. The ability to adjust model variations to promote representation was especially well-received. Moving forward, I see opportunities to refine the user interface to better support beginners, add real-time previews to make the design process more engaging, and introduce collaboration features to foster community feedback. Conducting more user testing with designers could also help uncover ways to further enhance the platform’s usability and creative experience.