Inspiration
We were fascinated by how chess visualizes strategic tension — every piece position tells a story about power, intent, and trajectory. We asked: what if a conversation had the same spatial structure, and you could see it?
What it does
Wio detects micro-signals of tension, defensiveness, and cooperation during a conversation and renders them as a live 3D field both speakers can see.
How we built it
We used LLM-based intent analysis to map each utterance onto semantic axes, then visualized the output as a dynamic 3D spatial field. Research was generated by deploying multiple Claude agents across defined research questions, synthesized into our user personas and design decisions.
Challenges we ran into
Defining axes that felt meaningful rather than arbitrary was harder than expected — we went through many iterations before landing on Relational Orientation and Dialogic Stance. Translating abstract linguistic theory into something visually intuitive required constant re-grounding in the actual user scenario.
Accomplishments that we're proud of
We built a speculative tool that is grounded in real neuroscience, linguistics, and family conflict research — not just aesthetically interesting but intellectually defensible. The moment the 3D field clicked as a visual metaphor felt like the whole project came together.
What we learned
The hardest design problem wasn't the visualization — it was neutrality. Every design choice risked implying judgment, and we had to keep asking: does this show, or does this tell? We also learned that the most powerful insights came from the edges of our research, not the center.
What's next for Wio
We want to prototype the real-time detection layer with actual speech input and test it with parent-teen pairs in a controlled setting. The long-term vision is a tool that doesn't just show you the conversation you had, but helps you understand the one you meant to have.
Built With
- aftereffect
- claude
- figma
- figmamake
- javascript
- json
- premierepro
- three.js




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