Style Match

KKO Tech

Style Match

Launching Soon

Premium AI
Fashion & Outfit
Matching.

An innovative approach to styling powered by AI — delivering a personalized, next-generation mobile experience for iOS & Android.

Download on the App StoreGet it on Google Play
Style Match App
Style Match App

Role

Software Architect

Platform

iOS & Android

Year

2026

Stack

Flutter · Spring Boot · AWS · GPT-4 Vision

The Challenge

Eliminating Outfit Fatigue

Individual style is personal, yet finding the perfect match across a fragmented wardrobe is a complex cognitive task. Style Match was designed to eliminate "outfit fatigue" by leveraging AI to understand the nuances of personal fashion choices.

The Solution

Intelligent Matching Engine

By building a scalable integrated architecture, we've created a system that processes high-resolution garment images and provides real-time matching suggestions — blending computer vision for item detection with a sophisticated recommendation engine.

Style Match App
Style Match App
Features

The Experience

Elevating personal fashion through a curated set of intelligent tools designed for the modern wardrobe.

AI Predictive Match

Our neural engine learns your style preferences to suggest the perfect daily combinations.

Digital Wardrobe

A high-fidelity digital twin of your physical closet, accessible anywhere, anytime.

Trend Radar

Stay ahead with real-time fashion insights synced directly from global style hubs.

Smart Search

Find any garment in seconds using multi-parameter filters and visual recognition.

Performance Core

Zero-lag experience powered by a high-performance backend and Flutter frontend.

Secure Style Vault

Your personal data and style choices are protected by enterprise-grade encryption.

Engineering

System Architecture

A multi-layered stack engineered for high-availability, low-latency AI processing, and a seamless cross-platform experience.

Layer 01

Client Interface

Flutter / DartPrimary Mobile Application
Layer 02

Service Infrastructure

Spring Boot / JavaEnterprise Backend System
Layer 03

Intelligence Engine

AWS / GPT-4 VisionVision & Recommendation Hub
Process

The Workflow

Step-by-step engineering journey of how we transform raw user data into personalized fashion intelligence.

01

Data Capture

Secure upload of wardrobe assets via Flutter. Assets are streamed to encrypted AWS S3 buckets with real-time metadata indexing for instant retrieval.

02

AI Analysis

GPT-4 Vision API performs granular garment classification, color extraction, and style tagging via high-fidelity visual analysis.

03

Smart Matching

A hybrid recommendation engine cross-references user preferences with current trends to generate mathematically optimized outfit combinations.

Project: Style Match // Auth: KKO TECH