The project aims to develop an AI-driven event matchmaking and visualization engine designed to enhance networking experiences at events.

The system will suggest potential connections for attendees based on their goals, roles, and shared topics of interest. By integrating with event data and attendee lists or LinkedIn profiles, the system will provide personalized recommendations. A key feature of the project is the development of a visual cluster map, which will help attendees easily identify and approach potential connections, making networking less awkward and more efficient.

This project provides an opportunity for learners to apply their knowledge of AI, data integration, and data visualization to create a practical solution for real-world networking challenges.

The deliverables for this project include a functional events engine that integrates with event data and LinkedIn profiles.

Additionally, the team will develop a visual cluster map that effectively displays suggested connections.

The final deliverable will be a working git repo and a presentation detailing the system's design, implementation, and testing results, ensuring a complete understanding of the project's outcomes.