AI VIRTUAL TRY-ON
"Will this actually look good on me?"
E-commerce returns remain as high as 30–40% because studio product photos on models fail to show how fabric drapes on diverse real human bodies. However, hallucinated or overly flattered AI generations destroy customer trust.
Designing Trust Around AI Uncertainty. A seamless try-on journey: Upload photo → Select garment → Realistic drape mapping with fit confidence indicators → Side-by-side wardrobe comparison.
Designing Beyond Generative Hype
Fit Confidence Indicators
Instead of falsely claiming 100% precision, the UI displays explicit stretch, drape, and length fit confidence scores based on user height and measurements.
Side-by-Side Comparison
Allows users to toggle between multiple outfit combinations instantly, turning speculative browsing into confident purchase decisions.
Lighting & Pose Fallbacks
Detects poor upload lighting or extreme angles and provides gentle guided framing cues before running diffusion inference to ensure high-fidelity drape renders.
Expectation Calibration
Frames AI output as a realistic silhouette approximation rather than a guaranteed tailoring snapshot, protecting brand integrity and reducing post-purchase return regret.