ShopGenie AI

Inspiration

Starting an online business looks easy, but finding the right products, understanding customers, and creating marketing strategies can be difficult. We wanted to build an AI assistant that helps sellers make smarter decisions and start faster.

What it does

ShopGenie AI helps e-commerce sellers find profitable products, analyze market trends, calculate profit potential, and generate product descriptions and marketing ideas using AI.

How we built it

We built ShopGenie AI using:

Next.js and TypeScript for the frontend FastAPI and Python for the backend Gemini API for AI features LangChain for AI agents Machine Learning models for product and profit analysis PostgreSQL for data storage

Challenges we ran into

Connecting multiple AI features into one system Making AI recommendations useful and accurate Designing a simple experience for users

Accomplishments that we're proud of

Built an AI-powered assistant for e-commerce sellers Automated product research and marketing tasks Created a platform that saves time and helps users make better decisions

What we learned

We learned how to build AI-powered applications, work with LLM APIs, create AI agents, and solve real-world business problems using technology.

What's next for ShopGenie AI

We want to add real-time market analysis, supplier suggestions, better predictions, and make ShopGenie AI a complete AI partner for online businesses.

Built With

• agent
• apis
• cloud
• css
• fastapi
• gemini
• langchain
• next.js
• numpy
• postgresql
• python
• react
• rest
• scikit-learn
• tailwind
• typescript