Portfolio case study / FASHION TECH & E-COMMERCE
AI-Powered Virtual Try-On Mobile App
Engineered an advanced computer vision mobile application allowing shoppers to accurately visualize clothing fit, fabric drape, and sizing on their own body contours. Significantly reduced sizing hesitation and return volume.
Evidence context. This case study is based on supplied portfolio material. Company and product names identify the platform, technology, or operating environment referenced in that material; they do not by themselves identify a direct Integrate First client engagement or indicate endorsement.
Reported outcome profile
Evidence connected to a specific operating environment.
32% Drop
In overall product return rates due to fit.
2.2x Higher
Add-to-cart rate when using virtual try-on.
88% Accuracy
Sizing accuracy score rated by buyers.
Reported in the supplied Enterprise Technology Case Studies Portfolio. Outcomes are engagement-specific and are not a guarantee of future performance.
Integrate First delivery perspective
A delivery pattern to pressure-test.
The challenge is not only rendering an effect. It is designing the data, performance, privacy, and product decision around it.
This is Integrate First’s original planning perspective. It is not presented as a reported element of the portfolio engagement.
Indicative delivery pattern
- 01
Define the customer confidence problem
- 02
Model the product and interaction states
- 03
Plan device, privacy, and performance constraints
- 04
Connect experience signals to product and growth decisions
Technology referenced in the portfolio
A first working session
Start with the customer uncertainty that most often delays a purchase or creates a return.
“Returns were our single biggest margin drain. This virtual try-on tech gave our shoppers the confidence to pick the right fit on the first try.”
— Head of Digital Customer Experience