I drove the end to end redesign of Retouched.ai, transforming an AI powered background removal tool into an intuitive web app that increased premium conversion by 200% and scaled usage to 60,000 images processed yearly.

Retouched.ai possessed a powerful AI image processing engine, but its complex, technical interface was alienating everyday users. The platform suffered from low conversion rates and high abandonment during onboarding because users felt overwhelmed.

200% increase in premium conversion

92% workflow task success rate

86% reduction in measured friction

4.6/5 user satisfaction rating

Retouched AI Overview

Before pushing pixels, I defined the business problem. The goal wasn't just to make the app look better—it was to dismantle technical friction that was actively preventing user adoption and monetization.

A comprehensive UX/UI redesign of Retouched.ai aimed at turning a confusing, overly technical product into a consumer-friendly application. The main goal was to simplify the flow, reduce confusion, and make it obvious what users needed to do next.

/ Convert technical friction into a guided introductory flow. / Implement progressive disclosure to reveal advanced AI tools without overwhelming users. / Establish a trustworthy visual identity to drive retention.

/ Navigating a rigid legacy codebase that resisted structural changes. / Simplifying UI animations to maintain performance under strict ML model limitations. / Designing around API latency for real time capabilities.

To understand why users were dropping off, I audited the existing experience. I led 15 discovery interviews and a competitive teardown of 8 industry leaders. This wasn't about validating features; it was about identifying the emotional and functional barriers driving churn.

"The AI parameters are intimidating." "I do not really see the point of this app." "I’m not trusting this site with my photos." We identified that cognitive overload and lack of trust were our primary conversion blockers.

I drove cross functional alignment by rapidly prototyping solutions. I utilized journey mapping and structural exercises to define a new product architecture that prioritized user comprehension over exposing raw ML capabilities.

With three engineers and a three month clock, a Figma file alone was not going to get us across the finish line. I stood up a design system that lived in both design and code — using AI tooling and a Model Context Protocol server to push Figma components straight into Tailwind. Engineers could pull a one to one match of what I designed instead of rebuilding each component by hand.

I also ran tight syncs with engineering and stakeholders so we stayed aligned on what shipped first. That collaboration cleared 95% of UI issues on the first QA pass and kept the redesign on schedule.

Here is how we transformed the product. Every design decision was anchored in reducing cognitive load, building trust, and driving users toward successful task completion.

200% Premium Conversion - Driven directly by progressively disclosing paid capabilities within the simplified workflow.

92% Task Success - Achieved for standard editing workflows, representing a 25% improvement over the legacy platform.

86% Reduced Friction - Achieved by streamlining the ordering pipeline and introducing real time visual feedback.

4.6/5 User Satisfaction - Overall platform user satisfaction scores surged from 3.4/5 post redesign, with a 40% boost in onboarding completion.