Bad fit is bleeding pet e-commerce.
Pet wear is still sold on S–M–L guesswork. Ill-fitting products come back — as returns, refunds, and dogs that simply refuse to wear them. Sizing is the single largest point of failure between a pet brand and a repeat customer.
A photo goes in. A perfect fit comes out.
Four steps, one unbroken data path — the owner scans a dog, our models turn it into a fit spec, and that spec becomes a size recommendation ready for the brand's platform. No tape measure, no size chart, no guesswork.
Scan
The owner scans the paw. Guided capture collects clean, multi-angle input.
Data
A 3D mesh is reconstructed and matched against breed-aware biometric models.
Fit
The system generates a validated size and true-fit recommendation for the product.
Recommend size
The platform returns the exact recommended size and fit spec — ready to plug into the brand's sizing, checkout, or fulfillment.
Three modules. One system.
Each product owns a layer of the stack — capture, data, product — and every layer speaks to the next.
One parametric model of the dog. Every category of fit.
Every scan feeds a parametric model of canine anatomy — a SMAL-style body model that encodes each dog's size, shape, and proportions. We start at the paw for footwear, then extend the same model to the neck, chest, and torso. Each new region the model learns to measure unlocks another product category on one sizing platform.