Inspiration - The day- to- day difficulty of locating products in a supermarket and the awkwardness of sales persons following us to guide.
What it does - The chatbot provides row and aisle location of each product and also gives recipes if asked allong with the locations of the ingredients.
How we built it- Backend consists of node.js,express,used pineconeDB for vector data storage, used rag framework and Gemini API for AI integration and used figma for UI building.
Challenges we ran into - Implementation of vectorDB and RAG.
Accomplishments that we're proud of- successful integration of backend
What we learned - Web development, figma , teamwork and collaboration
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