The goal of this project is to use AI to better understand our over 26,000 SKU's, our buyers who have purchased the products, what categories they are in, and what they may be interested in purchasing from our existing inventory. This will involve several different steps for the students, including:

- Analyzing our existing dataset of SKU's, buyers, and categories.

- Developing an AI-powered recommendation system to suggest products to buyers based on their past purchases and preferences.

- Optimizing software runtime performance and assessing areas for improvement.

- Researching other variables that can improve the quality of product recommendations.

- Accounting for additional variables in the recommendation engine software.

- Testing the developed software and making improvements based on additional data.

By the end of the project, students should demonstrate:

- Understanding of our existing dataset of SKU's, buyers, and categories.

- Understanding of variables that affect the quality of product recommendations.

- Identification of areas for future improvement of the software.

Bonus steps would include:

- Testing the developed software with users and accounting for additional parameters.

Final deliverables should include:

- All source code.

- A written report explaining the design process and outcomes.

Training, Education, Recommendation Letters, Experience working with a Silicon Valley Backed US Venture Startup and possible paid position following project delivery.

We are in the process of raising capital.