AI-Powered Multi-Tenant QR Ordering Platform

A secure multi-tenant QR ordering platform that uses OpenAI GPT-5.6 to transform restaurant operations and sales data into actionable business insights.

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Overview

AI-Powered Multi-Tenant QR Ordering Platform is a secure SaaS solution designed for restaurants and cafés.

Customers scan a QR code to browse the menu and place orders directly from their table without installing an application. Each business operates in an isolated tenant, ensuring complete data separation and security.

The platform also uses OpenAI GPT-5.6 to transform operational restaurant data into meaningful business insights instead of only displaying raw statistics.

Inspiration

Many restaurants already have QR menus, but they usually stop at taking orders. Restaurant owners still need to manually interpret sales reports, customer behavior, and operational performance.

I wanted to build a platform that not only manages orders but also helps business owners understand their business through AI-generated analysis.

What it does

The platform provides:

  • Multi-tenant restaurant management
  • QR-based ordering
  • Secure customer sessions
  • Start PIN protected table sessions
  • Reconnect PIN for secure device recovery
  • Real-time order management
  • Menu and product management
  • Sales reporting
  • AI Business Analysis powered by OpenAI GPT-5.6

Instead of sending raw database records, the backend calculates business metrics and sends only summarized information to GPT-5.6. The AI then generates actionable recommendations for restaurant owners.

How I built it

Backend

  • Java 17
  • Spring Boot
  • Spring Security
  • Spring Data JPA
  • PostgreSQL
  • Docker

Frontend

  • React
  • TypeScript
  • Vite

AI

  • OpenAI GPT-5.6
  • Codex

The application uses a schema-per-tenant architecture where every restaurant has its own isolated database schema.

Challenges

The biggest challenge was designing a secure public ordering experience.

Customers access the system using QR codes, which required solving:

  • secure session ownership
  • tenant isolation
  • session recovery
  • replay protection
  • device takeover prevention

Another challenge was integrating AI in a useful way. Rather than asking GPT to analyze raw database records, the backend prepares structured business metrics and GPT focuses on generating valuable insights.

Accomplishments

  • Fully working SaaS architecture
  • Secure multi-tenant implementation
  • AI-powered business analysis
  • Docker deployment
  • Production-ready backend
  • Secure QR ordering workflow

What I learned

This project significantly improved my experience in:

  • Spring Boot architecture
  • SaaS development
  • AI integration
  • Prompt engineering
  • Security design
  • Docker deployment
  • Production software development

What's next

Future plans include:

  • Inventory forecasting
  • Demand prediction
  • Personalized recommendations
  • AI-powered menu optimization
  • Revenue forecasting
  • Voice ordering

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