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Created by team RAGistan on April 19, 2024

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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