Role:
Participant - Session AI
Quick Facts:
∎ Collaborated with two teammates to prototype a location-based AI networking tool for events.
∎ Session AI utilizes AI recommendations to connect users with curated professional matches.
∎ Designed for live events, leveraging user profiles, preferences, and real-time location data.
∎ Facilitates follow-up networking through a personalized dashboard with smart reminders.
Session AI was a hackathon project with a mission to make networking at events more efficient and meaningful. By analyzing attendees’ professional profiles, shared interests, and proximity within the venue, Session AI offered curated match suggestions, helping users discover connections with shared interests. Traditional networking events often lead to missed opportunities and superficial interactions, so we designed Session AI as a “serendipity facilitator” that guided users toward valuable connections, making networking smarter and more purposeful. This prototype aimed to demonstrate how AI could enhance the experience, even in its early stages.
At the Berkeley AI Hackathon, we built a working prototype showcasing Session AI’s potential through features like a dynamic recommendation engine, location-based check-ins, and AI-generated conversation starters. When users checked in at the event, Session AI suggested top matches and provided conversation prompts tailored to shared interests. We also developed a dashboard that tracked networking stats, managed connections, and notified users about future events matching their goals. The project was a testament to the potential of AI in professional networking and sparked in me a deeper interest in the power of AI to create meaningful, real-world connections.
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