Use Cases
Fullstack Developer
Stack
Database
PostgreSQL
# Short Explanation
Nemu AI is web platform designed to help people quickly recover lost items by leveraging AI, Users can upload images and descriptions of lost or found items and system automatically tags and categorizes them.The AI then compares lost and found reports using image recognition and natural language processing (NLP) to suggest possible matches. With notifications and search features, Nemu reduces the manual effort of searching and significantly improves the chances of reuniting people with their belongings.
# Project Goals
The goal of this project was to implement everything we learned during the Full-Stack Web Developer bootcamp into a real product. Collaborating through GitHub, we built Nemu-AI, a lost & found platform leveraging Next.js, databases, authentication, deployment, and AI integration for auto-tagging and item matching. This project serves as proof that our learning could be transformed into a practical digital solution, with Samuel Sitorus as the master planner guiding the project’s direction.
# Tech Stack Used
In this project we used Next.js and JavaScript as the main framework and logic layer, styled with Tailwind CSS, and enhanced the interface using the HeroUI component library. For authentication, we implemented Arctic with Google OAuth and JWT Session to handle secure user access. Image uploads were managed through Cloudflare R2 static storage, while AI-powered tagging and categorization were integrated using OpenRouter. The project’s data layer relied on PostgreSQL with Neon DB, ensuring reliable and scalable storage for lost and found reports. Finally, the application was deployed on Vercel, providing fast, scalable, and seamless hosting.
# App Screenshots
