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One of the biggest challenges online shoppers face today is finding the best deal for a product across multiple websites. Prices vary widely between e-commerce platforms, and many times users miss out on additional discounts, coupons, or bank offers simply because they are not aware of them. This leads to overspending and a frustrating shopping experience. My idea is to build an AI-powered website that searches the web for a specific product and returns not only the site with the lowest base price, but also calculates the best possible price after applying available offers. For example, the system would factor in bank discounts, coupon codes, seasonal deals, or cashback opportunities, and display a step-by-step guide on how to claim them. Current solutions like price comparison sites only display raw prices without considering applicable offers or dynamic discounts. This gap makes it difficult for users to know the actual lowest price they can pay. My solution bridges this gap by combining real-time web scraping, AI-based deal recognition, and optimization algorithms to give the user the most cost-effective purchase path. The primary beneficiaries are online shoppers, especially students, working professionals, and families looking to save money on essentials or gadgets. In the long term, this tool can foster smarter consumption habits, reduce impulsive buying, and increase trust in digital shopping. This problem matters to me because I have often spent hours comparing prices manually, only to realize later that I missed a better offer. An AI-based assistant that ensures transparency and savings will save both time and money, making online shopping stress-free.
