PlateProfit AI：以開源 AI 將食物浪費轉化為利潤

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What I Built

PlateProfit AI is an AI-powered restaurant management concept designed to help restaurants make smarter decisions, reduce food waste, and protect their profits.

Restaurants often struggle with food waste, fluctuating ingredient costs, inventory management, and hidden profit leaks. Ingredients expire, purchasing decisions become difficult, and small inefficiencies can add up to significant financial losses.

PlateProfit AI aims to bring these challenges into one place. The goal is to help restaurant owners understand their costs, identify potential waste, analyze profitability, and make more informed operational decisions.

🍽️ Who is it for?

• Independent restaurant and café owners
• Small food businesses and cloud kitchens
• Restaurant managers responsible for inventory and costs
• Food entrepreneurs looking to improve operational efficiency

💡 Who would pay for it?

Restaurant owners and food businesses could pay for a tool that helps them control ingredient costs, reduce avoidable waste, and make better purchasing decisions. The long-term vision is to offer a practical, affordable solution that helps restaurants improve profitability while using their resources more efficiently.

My goal with PlateProfit AI is simple: help food businesses waste less, understand their numbers better, and turn smarter decisions into better profits.

Demo

Explore the live application and see the project in action.

Code

Check out the source code, explore the implementation, and follow the project's development.

How I Built It

I built PlateProfit AI as a web application focused on solving real-world challenges in restaurant operations, food waste, and profitability.

🛠️ Technology Stack

• Next.js 16 — For building the web application and server-side API routes.
• TypeScript — For type-safe development and more maintainable code.
• Ollama — For integrating with locally hosted AI models through an open-source AI workflow.

🧠 Building Around Open-Source AI

Rather than treating AI as just another chatbot, my goal was to make it useful for a specific business problem: helping food businesses make better operational and financial decisions.

The application includes API routes for Ollama analysis and service-status checks. This provides a foundation for connecting AI capabilities to restaurant-focused workflows.

🚀 My Development Approach

I focused on building a working web application, connecting the frontend with backend API routes, and preparing the project for deployment.

The project is deployed on Vercel, and the source code is available on GitHub so others can explore the implementation.

For me, this project is an opportunity to explore how open-source AI can make practical business tools more accessible to smaller food businesses — without making expensive AI infrastructure a prerequisite for innovation.

Why Does Open Innovation Matter?

I believe powerful AI tools shouldn't be accessible only to companies with large budgets. Small restaurants, cafés, and independent food businesses also deserve access to technology that can help them make smarter decisions.

That's why open innovation matters to PlateProfit AI.

By exploring Ollama and open-source AI models, I could experiment with locally hosted AI workflows instead of relying entirely on a proprietary AI API. This opens up possibilities for greater control over model selection, privacy-conscious processing, and reduced dependence on a single provider.

Open-source tools also make experimentation more accessible. Developers can inspect implementations, customize workflows, test different models, and learn from the wider community rather than building everything from scratch.

For a project focused on restaurant profitability and food waste, these advantages matter. The long-term vision is to make useful AI-powered business tools more accessible to smaller food businesses, where every operational improvement can count.

Open innovation makes it possible to build, experiment, share, and improve together. PlateProfit AI is my attempt to explore how that collaborative approach can turn AI into something practical for real-world businesses.

Prize Categories

I'm focusing on building a practical AI-powered solution for restaurant profitability and food waste reduction. I'll enter partner prize categories only where PlateProfit AI meets the specific requirements through actual implementation.