SmartStock AI 구축: Django, LangChain 및 멀티 에이전트 워크플로우를 통한 AI 기반 인벤토리 관리 플랫폼

Over the past few months, I’ve been exploring how AI can move beyond chatbots and become an active part of business workflows.

That journey led me to build SmartStock AI, an inventory management platform that combines modern web technologies with AI agents, Retrieval-Augmented Generation (RAG), demand forecasting, and automation.

Instead of only tracking inventory, SmartStock AI helps businesses make proactive decisions.

What SmartStock AI Can Do

• 🤖 Forecast future product demand
• 📦 Recommend purchasing decisions through AI agents
• 📚 Answer inventory-related questions using Hybrid RAG with source citations
• 📄 Process invoices using multimodal AI
• ⚡ Generate real-time inventory alerts
• 🔐 Secure the platform with JWT authentication and role-based access control

Technology Stack

Frontend

• React 19

Backend

• Django 5
• Django REST Framework

Database

• PostgreSQL
• pgvector

AI

• LangChain
• Hybrid RAG
• AI Agents
• Prophet Forecasting

Infrastructure

• Celery
• Redis
• Docker
• GitHub Actions

What I Learned

Building SmartStock AI taught me much more than integrating an LLM into an application.

Some of the biggest lessons were:

• Designing AI features that solve real business problems.
• Building reliable agent workflows instead of simple chatbot interactions.
• Combining vector search with structured database queries.
• Managing asynchronous AI tasks using Celery and Redis.
• Creating production-ready APIs with Django REST Framework.
• Deploying and maintaining a modern full-stack application.

Demo

🎥 YouTube Demo

https://www.youtube.com/watch?v=DQJqs6bgE98

🌐 Live Demo

https://smart-stock-dev.vercel.app/

Demo Account

Email: [email protected]

Password: Viewer123!

💻 GitHub Repository

https://github.com/Eng-Ayman-Mohamed/SmartStock-AI

Final Thoughts

This project was developed as my graduation project during the Information Technology Institute (ITI) Full Stack Web & Generative AI Program.

It was an incredible opportunity to explore AI engineering, backend architecture, and modern software development while building a practical product.

I’m continuing to learn about Agentic AI, RAG systems, and intelligent automation, and I plan to share more technical articles about what I build and what I learn.

If you have any feedback or ideas for improving SmartStock AI, I’d love to hear them!