Generative AI Hackathon with IBM Granite

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Amplifying human creativity and ingenuity

Binary Solvers

bhushansah

Roshan9

jhashubham09

Sensei-Search is a multimodal AI-powered search engine that enables users to query datasets using text, images, and voice. Built using IBM Granite models and the Retrieval-Augmented Generation (RAG) framework, the system enhances search accuracy by integrating LLMs with external knowledge sources. It leverages IBM Watsonx.ai for intelligent responses and Neo4j for knowledge graph-based fact-checking. Designed for businesses, Sensei-Search helps in faster decision-making and smart information retrieval across diverse domains. The project is deployed as both a web and mobile application using Streamlit.

Sensei-Search is an AI-driven multimodal search engine using IBM Granite models and RAG framework, enabling text, image, and voice queries.

"Binary Solvers team on Generative AI Hackathon with IBM Granite Hackathon"

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