GigEfx Labs aims to enhance its shopping intelligence app by integrating a web scraping solution that provides users with real-time shopping insights. The current app lacks the capability to gather and update shopping data dynamically, which limits its effectiveness in offering timely and relevant information to users. The goal of this project is to develop a robust web scraping tool that can extract data from various e-commerce websites, focusing on product prices, availability, and user reviews. This tool will enable the app to deliver up-to-date shopping solutions, enhancing user experience and engagement. The project will involve researching suitable web scraping technologies, designing a scalable scraping architecture, and ensuring compliance with legal and ethical standards in data collection. The solution should be efficient, reliable, and easy to integrate with the existing app infrastructure.

The project deliverables include a fully functional web scraping tool that integrates seamlessly with the GigEfx Labs shopping intelligence app. The tool should be capable of extracting and updating product data in real-time. Additionally, documentation detailing the scraping process, data sources, and integration steps will be provided. The deliverables will also include a testing report demonstrating the tool's effectiveness and reliability across multiple e-commerce platforms.