Quackly Private Limited
Tuniff: AI Hairstyle Recommendation App
An AI-powered mobile app that helps people choose a hairstyle that suits them, with a virtual try-on.
- Role
- UI/UX Design Intern
- Timeline
- March 2023 to April 2024
- Tools
- Figma, Google Forms
- Type
- Employer
The problem
Choosing a hairstyle lacks personalization. People struggle to picture how a style will suit their face shape before committing at the barber.
My role and constraints
As UI/UX Design Intern at Quackly, I led the end-to-end UX, from survey research and personas to information architecture and high-fidelity screens. Facial data is sensitive, so privacy and permissions had to be designed in, not added later.
Process
Survey research with 10 users: 8 of 10 surveyed users wanted AI personalisation, and 7 of 10 had privacy concerns about facial data.
Discover (research and competitive analysis), define (personas and MoSCoW), ideate (information architecture and user flows), then design (style guide and type).
Process
Discover
Survey research and competitive analysis.
Define
Personas and MoSCoW prioritization.
Ideate
Information architecture and user flows.
Design
Style guide, type and 14+ high-fidelity screens.
What the research said
Persona
Sneha Sharma
A tech-savvy designer looking for style changes that fit her creative image.
Finding
8 of 10 wanted AI personalisation
Out of 10 surveyed users.
Finding
7 of 10 had privacy concerns
About facial data, so privacy and permissions were designed in from the start.
The solution
A high-fidelity mobile prototype with guided onboarding, filtering, a 2D virtual try-on based on facial feature scanning, and clear privacy and permission controls.
Outcome
- Surveyed users wanted AI personalisation
- 8 of 10
- Had privacy concerns
- 7 of 10
- High-fidelity screens
- 14+
What I learned
Biometric data needs radical transparency in privacy settings, and a minimal UI keeps complex AI output from overwhelming people.