AI-assisted inspiration archive that helps creatives rediscover the thinking behind what they save
Role:
UX Researcher & Product Designer
Timeline:
Sep - Dec 2025
Tools:
Figma,
CSS/HTML,
React
Adobe CC
Team:
Amy Choi,
Bilge Kosem Ilhan,
Jodie Yang
Core Problem Space
Creative practitioners frequently gather diverse inspirational content, but:
Materials become scattered across many platforms
Collections grow rapidly and become hard to revisit and recall
The meaning behind why something was saved often fades over time.
Current tools support storage but not sensemaking
Many AI tools shortcut creativity with instant outputs
Our Approach
We designed a supportive AI system that scaffolds creativity and reflection by:
Encouraging reflective tagging at the moment of collection
Interpreting formal, emotional, and conceptual language
Organizing materials into interconnected visual networks
Surfacing hidden patterns and relationships
Preserving creative ownership
Design Principles
From our research, we developed six emergent design principles:
The System
We prioritize foundational interactions with plans to expand advanced search, clustering, collaboration, and multimodal input in subsequent phases.
On the homepage, users can zoom in and out to see their full collection. Hovering over and clicking on the image allows users to see tags attached at a glance.
When users upload a media, the system guides them through a two prompt tagging interface. Users can input custom tags, shuffle AI suggestions, or move freely between prompts. Tagged images appear in the home canvas with tags accessible on hover/click.
Research & Discovery
R1: How can we encourage people to describe inspirational content in ways that can reveal useful creative connections that people might otherwise miss?
R2: In what ways can AI structure and visualize inspiration to provide interconnected mapping of knowledge for easier retrieval and reflection?
METHODS
Literature review
↓
Interview
↓
Wizard of oz experiments
KEY FINDINGS
Fragmented Inspiration Ecosystems:
Users’ current ways of collecting inspiration are decentralized and spread across 3-5+ different platforms, making materials hard to maintain and revisit.
“ Everything’s everywhere. I keep hoping I’ll go back and sort it all someday.”
→ Need centralized system with cross-platform import capabilities
Dual collection modes:
Intentional/project-driven vs. spontaneous/curiosity-driven.
→ system must accommodate both structures and exploratory workflows
Tagging as reflection & friction:
Tagging encourages deeper thinking about content significance and relevance, but feels constraining (vocabulary) or effortful.
“It’s easier to just talk in sentences.”
→ Support conversational and flexible language, offer AI suggestions after user’s initial input
Clustering Tension (insight vs. agency):
Manual clustering supports personal meaning making and meaningful organization. AI-assisted clustering provides new perspectives but can override user logic.
"If I could use AI-generated buckets across everything, I’d stop changing folders."
"No... I wouldn’t have grouped them like this."
→ Enable fluid, editable clustering where users can accept, modify, or reject AI suggestions
Users want supportive AI:
Participants valued AI that interprets and suggests, but want final control.
→ Design for balanced agency