🚀AI Hackathon: Build real-world healthcare solutions with AI
Join us for an in-person hackathon exploring how modern AI technologies can be applied to real-world healthcare challenges.
This event is designed for builders who want to move beyond demos and create practical, end-to-end solutions — from idea to working prototype.
Whether you’re an engineer, data practitioner, student, or AI enthusiast, this is an opportunity to collaborate, build, and showcase impactful work.
📅 Event Timeline
Kickoff & Team Formation
🗓 March 7, 2026
📍 University of Toronto
OISE Building – Room 2214
252 Bloor St W, Toronto
Meet fellow builders, form teams, and get aligned on the challenge. We’ll walk through problem framing, technical expectations, and set the direction for the build phase.
Build Week (Async)
Teams will continue building over the following week, allowing time for deeper implementation, iteration, and refinement.
Final Presentations & Networking
🗓 March 13, 2026
Top teams will present their projects live, followed by winner announcements and curated networking with industry professionals across AI and healthcare.
🧠 Focus Areas
Projects will explore the intersection of Healthcare × AI, including:
AI agents & workflow automation
Retrieval-augmented generation (RAG)
Decision-support systems
Production-oriented architectures
Specific problem statements will be released closer to kickoff.
🏆 Prize Pool
$1,000 CAD will be awarded to the most innovative and impactful projects.
🤝 Sponsored By
This hackathon is supported by VS Consulting Group and Predictiv AI Inc., organizations actively building and investing in AI-driven solutions.
Representatives from our supporting partners will be present throughout the event — participating in judging, engaging in networking sessions, and connecting directly with participants.
Attendees will have the opportunity to build relationships with industry professionals and may be considered for future hiring opportunities based on project strength and engagement.
👥 Who Should Attend
Builders, students, engineers, and data practitioners excited about applying AI to meaningful real-world problems.
No prior healthcare experience required — just curiosity and a willingness to build.