Saqlain Abid@saqlainabid

The idea is to use Gemini's power of multi-modal power to get a better idea of a product using pictures, text, and documents. Our system will use Gemini AI to analyze product descriptions, and Compare different products and identify the best value proposition. Review product reviews by previous buyers and the repeat purchasing pattern by the same buyer. Recommend superior alternatives based on user preferences and market trends. Allow users to input information about their personality traits for personalized recommendations. Provide an insightful report explaining the reasoning behind each recommendation. Feature a chatbot interface to guide users through the product evaluation process. Product description could be provided through various means like:- URL of the product page, PDF copy of Product Description, Photo of Product itself, A click on the product page through a Chrome Plug-in, or pre-integrated in an e-commerce site, or in a mobile shopping app, where a photo of the product could be taken in real-time

Using Vectara and Llamaindex we process tabular data using multiple models to get extremely accurate recommendations. Our solution can scrape product information from any e-commerce platform such as Amazon, Walmart, eBay, etc., and use RAG to incorporate customer-specific preferences to find out the best suitable products for price, features, ratings, etc. The solution facilitates the hybrid search mechanism i.e. keyword as well as semantic search capabilities. It also supports summarization for products e.g. concerning sales, trends, revenue, etc. The next steps are using a voice-enabled chatbot, and an alerting mechanism with product search across internet.

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