fabric feel

Inspiration

We started with a simple observation: the moment shopping moved online, your hands went offline. Every other sense got a digital upgrade, i.e. higher resolution photos, 3D try-on, AR filters. But touch was just... abandoned. We became curious about what it would mean to restore and visualize that sense. The prompt pushed us to think beyond the traditional five senses, and texture felt like the most personal, underserved, and consequential one to explore. The environmental angle came naturally — once we understood that most fashion returns happen because people couldn't feel what they were buying, the waste story wrote itself.

What It Does

FabricFeel is a standalone fabric literacy platform that decompose the texture and let you experience it before purchasing online. You upload a fabric photo, and the product generates haptic feedback, unique soundscape, and a drawing canvas where the brush stroke physically simulate the fabric's feel under your finger. When in comparison mode, you can experience how fabric textures differ directly from interacting with the brush stroke drawing on the canvas.  At the end, you answer one question: does this feel like you? Both exits, yes and no, are designed with equal care, because knowing what doesn't feel right is just as valuable as knowing what does.

How We Built It

We started on FigJam to map how e-commerce platforms handle texture, what texture means to us as shoppers, and what interactions could make a digital surface feel physical. From that session we landed on a multimodal approach: sound, haptic drawing, and visual working simultaneously, the way the brain actually processes touch. We used Claude to generate a PRD, which became our blueprint for Figma Make. From there it was iteration, tuning the brush physics, finding the right visual language, and making sure every exit felt considered.

Challenges we ran into

The core challenge was the central question of the whole project: how do you let someone feel fabric without touching it? We explored visual, haptic, and audio feedback. But quickly realized that true haptic feedback is nearly impossible to convey on a standard phone screen. Rather than abandon the idea, we reframed it: the drawing canvas became our haptic proxy, and we added a haptic pattern graph to make the texture dimension visible even where it couldn't be directly felt. The second tension was between innovation and usability. We were proposing a genuinely new kind of sensory interface, but it still needed to feel immediately intuitive to someone who had never used anything like it. Every unconventional interaction had to earn its place by being learnable within seconds.

Accomplishments That We're Proud Of

We're proud of how FabricFeel came together as a complete experience. The flow feels intentional from the first tap to the final verdict. Breaking a fabric down into five parameters and translating each one into a distinct brush behavior was the technical bet we were least sure about, and it paid off. Rough linen and silk satin produce visibly and physically different strokes without any label or instruction — the user's hand just knows. That moment of wordless understanding is exactly what we were designing toward. We're also proud of the comparison mode. Letting users switch between fabrics gives them real agency, not just a passive experience, but an active one where they can feel the difference directly.

What We Learned

We learned a new way to work. Using AI to move from rough idea to structured PRD to interactive prototype showed us how fast the gap between thinking and building can close when the workflow is right. Sparkling an idea, sketching it out, and having something tangible to react to within hours. That speed changes how you design. But the speed also sharpened something else. AI can generate quickly, but it can't tell good design from bad. That judgment still has to come from us — knowing when a flow feels off, when a visual choice undermines the concept, when an interaction needs to be simpler. Learning to give precise, targeted feedback and hold onto our original vision through every iteration turned out to be just as important as any technical skill we used this weekend.

What's Next for FabricFeel

The most immediate next step is real fabric scanning — replacing the simulated texture profile with actual ML-based fiber analysis from a phone camera. Beyond that, the Feel Library is the feature we're excited about: a personal archive of every fabric you've felt, building a texture vocabulary unique to you over time.