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GrabBuddy project preview

GrabBuddy

List of technologies used:

HTML

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CSS

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TypeScript

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SvelteKit

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Tailwind

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Python

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PostgreSQL

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Figma

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Project description:

Attempted at creating an AI-powered solution using Ollama, Mistral (7b), and Gemini for the "Economic Empowerment through AI" domain prepared by Grab for UMHackathon 2025. This solution is designed to serve as a "buddy" for vendors and merchants, assisting them in making informed decisions for their stores by providing valuable insights through a streamlined dashboard. The dashboard is powered by AI, which interprets and explains data in natural language, making it accessible and actionable. Additionally, the solution harnesses the capabilities of AI to summarize reviews of competitor stores, enabling merchants to gather comprehensive feedback on consumer expectations. Merchants can engage in natural language conversations with the AI to obtain insights regarding their store's statistics, including inventory management and receipt processing. This interactive feature enhances the decision-making process, ultimately contributing to the economic empowerment of the merchants. The team, named 418, consisted of 4 members: Joshua Edwin Rene Bonham, Alex Chee Kai Hong, Justin Yong Wenn Weii, and myself.