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User / data flow diagrams
Graduates
Bri Mai
BS in Interaction Design — Interaction DesignCourse:
Emerging Tech: AI
Faculty:
Mehar Nangia
Term:
2025 Summer
Arc (AI-powered setlist builder)
Arc is an interactive, AI-assisted setlist tool for iPadOS that helps music artists craft data-informed, emotionally resonant live performances. Using LLM-powered recommendations and real-time audience sentiment monitoring, Arc gives artists full creative control while leveraging their streaming and social data to build and refine their setlist's emotional arc.
Process:
Starting from a personal observation as both a music artist and live show attendee, I conducted market research into the tools indie artists rely on to prepare for live shows — and found a clear gap: while distribution and visual tools have evolved, setlist strategy remains largely manual. I mapped a full user journey from show booking to post-performance, developed a user/data flow diagram to identify where AI inputs were most critical, and built a persona around a rising indie artist navigating her first large-scale shows. From there I moved into wireframes, iterated on core interaction patterns (including a node-based setlist board and a live sentiment capture flow), and developed Arc's full visual identity and design system.
Learning Outcomes:
This project deepened my understanding of how to design AI as a collaborator rather than a replacement, particularly in creative, high-stakes contexts where user trust and data transparency are essential. I learned how to make data flows a design constraint from the start, not an afterthought, and how to balance AI-generated suggestions with meaningful user control. I also gained experience designing for an underserved, domain-specific user — indie artists — which pushed me to ground every design decision in real behavioral research rather than assumptions.
Project Website: