AI-Powered Visual Search

Find any shoe in seconds, not shelves

Take a picture of any shoe and instantly find its matching catalog design, material details, and exact shelf location. No more manual searching through unlabelled inventory boxes.

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ShoeMatch AI Catalog Sample SHOE-001
Simple 5-Step Process

How Workers Find Any Shoe Instantly

No technical training required. Your warehouse team simply snaps a photo and gets the exact location in seconds.

Sport Athletic Sample
01

1. Snap Photo

Take a photo of any shoe on the warehouse floor using a phone or tablet.

02

2. Cleans Background

The app automatically removes background floor clutter to focus only on the shoe.

03

3. Reads Shape & Texture

Analyzes unique stitching, sole patterns, and materials in less than a second.

04

4. Smart Quality Check

Gently lets workers know if an accidental non-shoe photo was taken.

05

5. Shows Shelf Rack

Displays the exact matching shoe along with its building, rack, and shelf location.

Reliable & Fast

High Accuracy Built for Real Warehouse Floors

Traditional color search fails under warehouse overhead lights. Our visual search focuses on shoe shape, textures, and stitching for dependable results.

Sub-Second Speed (~38ms)

Search results display almost instantly so your staff never waits around during busy warehouse shifts.

Handles Any Camera Angle

Whether a phone photo is taken straight-on, sideways, or tilted, the app correctly identifies the shoe model.

Filters Out Non-Shoes

Accidental photos of slippers or non-footwear objects are flagged immediately so your database remains clean.

Warehouse Workflow

Say Goodbye to Hunting Through Unlabelled Boxes

Compare the old manual searching process with point-and-shoot visual location.

Black Leather Oxford Sample
The Old Manual Way
  • Workers waste 15 to 25 minutes walking aisles searching for sample shoes.
  • Opening dozens of unlabelled boxes manually just to check the shoe style.
  • Lost sample shoes and mislabeled box tags cause costly shipping delays.
The ShoeMatch AI Way
  • Snap a photo on a phone or tablet and get matching results in under 1 second.
  • Exact location details provided immediately: Building → Section → Rack → Shelf.
  • Includes complete product info like leather type, sole material, and season tag.
Multi-Platform Ready

Built for Factory & Warehouse Staff

Designed to work seamlessly on desktop computers, tablets, and mobile phones.

Use Phone Camera

Staff can take pictures directly using their Android phone camera while walking warehouse aisles.

Glove-Friendly Buttons

Large, easy-to-tap buttons designed specifically for factory workers wearing protective gloves.

Employee & Admin Roles

Secure sign-in with simple search access for workers and catalog management for managers.

Supplementary Overview

AI Technology Under the Hood

For technically curious visitors, here is the underlying artificial intelligence stack powering our visual search.

Visual AI Engine

DINOv2 Neural Network

Self-supervised vision model trained to recognize fine footwear textures and shapes regardless of lighting.

Background Isolation

U2-Netp Cutout Model

Lightweight image segmenter that removes background clutter before searching.

Vector Search Engine

FAISS Indexing

High-speed similarity search engine that scans thousands of catalog items in milliseconds.

FAQ

Frequently Asked Questions

The app automatically cleans up background clutter (like warehouse floor tiles, shelf racks, or hands) so it only focuses on matching the shoe itself.
ShoeMatch AI checks whether the photo contains actual footwear. If an accidental non-shoe photo or slipper is uploaded, the app politely lets the worker know to try again.
Yes! The app runs in any web browser and is also available as a native Android mobile application with single-tap camera controls.
Warehouse managers can upload sample photos along with product details (materials, season) and exact rack locations (Building, Section, Rack, Shelf).

Eliminate Warehouse Search Time Today

Deploy ShoeMatch AI across your warehouse team or test visual search in your browser right now.

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