🚀 Build AI : Build the Future

The McGill Data Network (MDN) x Boundary AI

Stop dreaming about the future—build it in four hours. The McGill Data Network is hosting a high-impact, fast-paced sprint designed to turn ambitious ideas into functional AI prototypes. Whether you're a seasoned coder or a data enthusiast, this is your chance to automate the world around you and kickstart your career.

 

🎯 The Challenge: Automate. Optimize. Innovate.

Your mission is to design an AI-powered system that replaces, enhances, or optimizes a manual task. Whether it's streamlining a complex workflow or automating a daily decision-making process, the goal is simple: Build a solution that makes human effort more efficient.

 

📅 Event Schedule (Thursday, April 2nd)

Location: McGill University | Time: 12:00 PM – 5:00 PM

Time Activity What's Happening
12:00 PM Kick-off Theme reveal and prompt details.
12:30 PM Development Phase 3.5 hours of high-speed hacking. Judges will be roaming for feedback!
4:00 PM Submission Deadline Hard stop. All projects must be on Devpost.
4:10 PM Round 1: Initial Judging The Jury shortlists the Top 5 Teams.
4:30 PM Round 2: Final Pitches The Top 5 deliver a 3-minute "Live Demo" pitch.
4:45 PM Awards & Closing Winners announced and internship opportunities discussed.

 

⚖️ Rules & Eligibility

  • Open to All Majors: If you can build it, we want to see it.

  • Quebec University Students: Must be currently enrolled in a Quebec institution.

  • Teams: Register as an individual or in teams of up to 3.

  • The Constraint: Your solution must use AI to optimize a manual task.

 

🛠️ Judging Criteria

  • Innovation: How creative is the automation?

  • Impact: How much time/effort does the solution actually save?

  • Technical Execution: How well does the AI prototype function under pressure?

  • The Pitch: Can you sell your vision in 180 seconds?

Requirements

🛠️ Submission Requirements

1. The Project "Why" (Text Description)

  • The Manual Task: Clearly describe the tedious or inefficient process you chose to automate.

  • The AI Solution: How does your system work? (e.g., “We used a GPT-4 API to parse PDFs” or “We built a CV model to detect inventory”).

  • The Impact: Estimate how much time or human effort your tool saves.

2. Proof of Code (GitHub Link)

  • A link to a public repository containing your source code.

  • Note: Ensure your README is updated with brief setup instructions so the judges can see how the magic happens.

3. The Working Prototype (Demo)

  • Live Link or Video: If your tool is a web app, provide a "Try it Out" link. If it’s a backend script or local tool, upload a 1-2 minute screen recording demonstrating the automation in action.

  • Before vs. After: Your demo should explicitly show the "Manual Way" vs. your new "Automated Way."

Hackathon Sponsors

Prizes

$CAD 300+ in prizes
+ other prizes
Summer Intership at BoundaryAI
1 winner

Outstanding participants will be fast-tracked for a Summer 2026 Internship opportunity. This is your chance to skip the resume pile and prove your skills directly to the engineering team. We are looking for hackers who can build fast, think critically about automation, and turn AI into real-world impact.

Gift cards
$CAD 300 in cash
1 winner

We are awarding three $100 gift cards to the top-performing teams/individuals. Whether you need to fuel your next project, upgrade your gear, or just celebrate a win, these prizes are yours for building the most impactful automation of the day.

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Marie-France Ouimet

Marie-France Ouimet
MAF - Accenture

Manon Vaisse

Manon Vaisse
Taskies

Sameer Borwankar

Sameer Borwankar
McGill University

Judging Criteria

  • Impact & Utility (25%)
    How significant is the "manual task" being automated? Does this solution actually save time, reduce errors, or lower costs in a meaningful way? The Question: If this were a real product, would someone pay to use it?
  • Technical Innovation (25%)
    How effectively did you use AI (LLMs, Computer Vision, Regression, etc.) to solve the problem? Is the code well-structured, or is it just a "wrapper"? The Question: Is the AI a core part of the solution, or just a buzzword?
  • Quality of the Prototype (25%)
    Does the automation actually work? How much "polish" did you manage to achieve in just 4 hours? The Question: Can we see a clear "Input → AI Logic → Automated Output" flow in the demo?
  • The Pitch & Communication (25%)
    Is the project description on Devpost clear and compelling? For the Top 5: Was the 3-minute live demo persuasive and easy to understand? The Question: Can you explain a complex technical solution to a non-technical stakeholder?

Questions? Email the hackathon manager

Tell your friends

Hackathon sponsors

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.