Traditional 2D optical capture technology was holding retailers back, leading to:

• Limited precision: Resulting in inaccurate sizing.
• High return rates: Causing dissatisfied customers.
• Declining sales: Due to reduced shopper engagement in both retail and wellness services.

We engineered a LiDAR-based 3D body scanning system to create precise human digital-twins and provide personalized fit recommendations. The solution followed a four-step process:

• LiDAR-based 3D Body Scanning: Captured detailed body measurements with millimeter accuracy while maintaining privacy through non-identifiable scanning.
• Human Digital Twin for Measurement: A digital twin algorithm mapped customer body dimensions to the closest-fit apparel across partnered brands.
• Personalized Fit Recommendations: The system generated personalized clothing suggestions by combining 3D scanning, AI, and AR, boosting buyer confidence.
• Privacy-First Approach: No photos or videos were stored — only encrypted, anonymized measurement data was used.

• 📈 6x Conversion Rate: Shoppers were 6 times more likely to complete purchases.
• 📉 80% Drop in Returns: Both in-store and online return rates decreased dramatically.
• 💰 25% Higher AOV: Customers purchased more confidently and added more to their carts.
• 🤝 2x Loyalty Sign-ups: More shoppers joined loyalty programs after using the tool.

• Intel RealSense LiDAR: For 3D scanning accuracy.
• PyTorch: For the AI/ML fit prediction engine.
• Unity: For real-time AR visualization & digital twin rendering.
• AWS: For cloud hosting, analytics, and secure data storage.

• Accurate, personalized sizing improved customer satisfaction.
• Reduced returns saved significant costs for the retailer.
• Boosted conversion rates and overall revenue.
• Created a trustworthy, privacy-first digital shopping experience.