The virtual try-on (VTO) market is projected to hit $15.29 billion in 2026. Yet, despite this explosive growth, only 1.4% of shoppers use it regularly.
Why? Because research consistently shows that 86.6% of consumers cite privacy concerns as a significant barrier. People want to see how clothes look on them, but they absolutely refuse to upload photos of their bodies to faceless corporate servers.
I'm building ACA, a virtual try-on tool with one core, non-negotiable promise:
Your photo never leaves your phone.
No permanent server storage. No data harvesting.
The Problem with Current VTO
Right now, the photo upload step is the critical gate in the VTO funnel. If it feels clunky, confusing, or invasive, the entire experience collapses. Most tools are either locked to a single retailer's ecosystem or require you to hand over biometric data to a third-party cloud.
The ACA Approach
I am building ACA to be a universal, privacy-first tool.
- Short-term: Validating the workflow with secure, ephemeral API processing (with clear, upfront consent).
- Long-term: Integrating on-device machine learning (like Mobile-VTON) so the inference happens entirely locally on your device.
I Need Your Feedback
Right now, I'm in the validation phase. I'm curious:
- If a tool let you see how a garment looked on you without requiring storing your image, would you use it?
- What is your biggest hesitation or frustration with current virtual try-on tools?
I'm building this entirely on a $150 phone, and I'll be sharing the technical journey (including the challenges of on-device ML and privacy-preserving architecture) right here.
Let me know your thoughts! 🐯👕
wishlist here : https://aca-landing.netlify.app/
Built from India for the world.