Generative AI Hackathon with IBM watsonx

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Essay

Sohaib Ahmed Abbasi

MeetAssist addresses common challenges associated with meetings, such as unclear goals, time wastage, and confusion about next steps. Research shows that a significant portion of employees’ time is spent in meetings and unproductive ones result in billions of dollars in annual losses. To address these problems, the solution is split into two phases: Pre-Meeting and Post-Meeting.

In the Pre-Meeting phase, MeetAssist helps users create detailed, goal-oriented agendas, ensuring every meeting starts with a well-defined purpose and clear objectives.

The Post-Meeting phase focuses on analyzing meeting transcripts to provide actionable insights. This includes summarizing key points, extracting action items, assessing participant sentiments, offering productivity analysis, and suggesting improvements to enhance future meetings.

MeetAssist aims to maximize the value derived from every meeting, benefiting both teams and individuals. It leverages the Llama 3 70B Instruct generative AI model from the IBM Watsonx platform for its core features. The tech stack used for it inludes Python with Flask for backend development, HTML, CSS, Bootstrap, and JavaScript for the frontend, Docker for containerization, and Render for hosting.

AI-powered productivity tool designed to make meetings more organized, effective, and insightful with features like agenda generation, action item extraction, sentiment analysis, and productivity insights to enhance outcomes.

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