The project involves developing a low-fidelity Minimum Viable Product (MVP) for PriceScout, an AI-powered price comparison database application. The goal is to create a tool that helps consumers find the best prices on products across various retailers by utilizing advanced algorithms to analyze market data. This project will allow learners to apply their knowledge of database management, AI algorithms, and user interface design. The MVP will focus on core functionalities, ensuring that the application can effectively gather and compare pricing data from multiple sources. The project will also provide an opportunity to explore the integration of AI technologies in consumer applications, enhancing the shopping experience for users. By the end of the project, learners will have a foundational understanding of developing AI-driven applications and the challenges involved in processing and presenting large datasets.

The deliverables for this project include a functional low-fidelity MVP of the PriceScout application. This will consist of a basic user interface, a database capable of storing and retrieving pricing data, and an algorithm that can compare prices across different retailers. Additionally, a brief report documenting the development process, challenges faced, and potential improvements for future iterations will be required. The project will culminate in a presentation demonstrating the MVP's capabilities and discussing the potential impact of AI in price comparison tools.