Software Development
FitFolio
An AI-assisted fashion catalog and social platform for discovering, reviewing, and curating clothing.
Summary
FitFolio is a full-stack fashion platform where users browse apparel, create collections and tier lists, write reviews, and discover items through semantic search and AI-powered metadata enrichment.
Overview
FitFolio is a fashion catalog and community platform built to help users discover clothing, share opinions, and organize style preferences.
Users can browse items by brand and category, follow other members, curate collections and tier lists, and leave structured reviews with fit, comfort, and quality ratings.
AI Discovery & Enrichment
A core part of FitFolio is its AI pipeline. When users upload product images, the backend uses OpenAI to extract fashion metadata such as style, occasion, and vibe tags.
A FastAPI ML service generates embeddings for semantic search, while review data can be aggregated into item insights — turning raw community feedback into searchable, structured product intelligence.
Technical Implementation
The main backend was built with Java 21 and Spring Boot, using PostgreSQL with Flyway migrations, session-based authentication, and AWS S3 for presigned image uploads. The frontend is a Next.js and React application.
A separate FastAPI ML service handles embeddings and review insights, while OpenAI powers image enrichment and natural-language smart search. The browser communicates only with the Java API, which orchestrates ML and third-party services server-side.
Impact
FitFolio demonstrates full-stack product development across catalog management, social features, and applied AI — from image enrichment and vector search to review aggregation and curated collections.
The project highlights modular backend design, multi-service architecture, cloud file handling, and practical ML integration in a consumer-facing fashion product.
Outcome
Delivered a production-oriented architecture with a Spring Boot API, FastAPI ML sidecar, and Next.js frontend — covering item enrichment, vector search, reviews/insights, and social curation features.