πAI Hackathon: Build real-world healthcare solutions with AI
βJoin us for an in-person hackathon exploring how modern AI technologies can be applied to real-world healthcare challenges.
βThis event is designed for builders who want to move beyond demos and create practical, end-to-end solutions β from idea to working prototype.
βWhether youβre an engineer, data practitioner, student, or AI enthusiast, this is an opportunity to collaborate, build, and showcase impactful work.
βπ Event Timeline
βKickoff & Team Formation
βπ March 7, 2026
βπ University of Toronto
βMeet fellow builders, form teams, and get aligned on the challenge. Weβll walk through problem framing, technical expectations, and set the direction for the build phase.
βBuild Week (Async)
βTeams will continue building over the following week, allowing time for deeper implementation, iteration, and refinement.
βFinal Presentations & Networking
βπ March 14, 2026
βTop teams will present their projects live, followed by winner announcements and curated networking with industry professionals across AI and healthcare.
βπ§ Focus Areas
βProjects will explore the intersection of Healthcare Γ AI, including:
βAI agents & workflow automation
βRetrieval-augmented generation (RAG)
βDecision-support systems
βProduction-oriented architectures
βSpecific problem statements will be released closer to kickoff.
βπ Prize Pool
β$1,000 CAD will be awarded to the most innovative and impactful projects.
βπ€ Sponsored By
βThis hackathon is supported by VS Consulting Group and Predictiv AI Inc., organizations actively building and investing in AI-driven solutions.
βRepresentatives from our supporting partners will be present throughout the event β participating in judging, engaging in networking sessions, and connecting directly with participants.
βAttendees will have the opportunity to build relationships with industry professionals and may be considered for future hiring opportunities based on project strength and engagement.
βπ₯ Who Should Attend
βBuilders, students, engineers, and data practitioners excited about applying AI to meaningful real-world problems.
βNo prior healthcare experience required β just curiosity and a willingness to build.