Dimenso provides an AI‑driven virtual try‑on platform that creates realistic 3D models of eyewear, watches, and jewelry from just two to three product photos and overlays them on a live video feed using real‑time face tracking. The solution integrates via SDKs with Shopify and custom websites, runs locally for privacy compliance, and supports both online stores and in‑store smart mirrors to boost conversion and reduce returns.
Funding
Funding not disclosed
Founders
Product
Problem
Online retailers of eyewear, watches, and jewelry often struggle to provide customers with an accurate way to visualize products on themselves, leading to high return rates and reduced conversion. Traditional 3D modeling requires extensive manual effort and large image sets, making it costly and time‑consuming to implement.
Solution
Dimenso offers an AI‑driven virtual try‑on platform that automatically generates realistic 3D models from just two to three product photos. The solution integrates via SDKs with Shopify and any custom website, enabling seamless embedding of the try‑on experience in online stores and in‑store smart mirrors. Real‑time face tracking using 468 facial landmarks runs at over 30 FPS, allowing users to see accurate overlays of eyewear, watches, or jewelry on their live video feed. All processing occurs locally on the device, ensuring no personal data is stored and maintaining GDPR and CCPA compliance. Retailers can quickly launch AR try‑ons without specialized 3D assets, improving shopper confidence and reducing returns.
Target Audience
Primary customers are e‑commerce retailers and brick‑and‑mortar stores selling eyewear, watches, or jewelry that want to add an AR try‑on experience to their sales channels.
Features
- AI‑powered generation of high‑fidelity 3D models from only 2–3 product images
- SDKs for Shopify and custom websites, enabling plug‑and‑play integration
- Support for multiple product categories: eyewear, watches, and jewelry
- Real‑time face tracking with 468 landmark detection at 30+ FPS for precise fit visualization
- Compatibility with both online storefronts and in‑store smart mirror deployments
- Privacy‑first architecture that processes data locally and does not store user information