The excitement in the air was undeniable as I joined hundreds of innovators at the Global Entrepreneur and Innovation Week (GEIW) Hackathon. This event was far from a typical coding competition; it was an intense burst of brainstorming, problem-solving, and boundary-pushing, all under a tight deadline.
Our first challenge was uniquely Moroccan: addressing drought. With only 48 hours to find a solution, our team focused on a promising idea—a Drought Prediction Platform. We envisioned a user-friendly tool leveraging data and analytics to forecast droughts, helping farmers and policymakers make informed decisions. Fueled by late-night caffeine, our coding sessions were both intense and exhilarating, and the strong sense of camaraderie drove us to create something impactful.
Advancing to the final phase brought an unmatched thrill. This time, the global challenge was phishing. We saw a chance to protect organizations and individuals with our solution: CleanBox, a Software-as-a-Service (SaaS) designed to secure email. CleanBox would serve as a protective mail server, filtering emails before they reached clients' inboxes, significantly reducing phishing risks.
The last 24 hours were a whirlwind of focused development, pitch refinement, and battling fatigue. Our determination to create a practical solution fueled every keystroke. When it was time to present, our nervous energy turned into a passionate demonstration of CleanBox.
Though we didn't win the final prize, the experience was transformative. GEIW wasn't just about winning; it was about the journey of innovation, the power of collaboration, and the excitement of bringing ideas to life. We tackled two very different challenges, sharpened our skills under pressure, and gained newfound confidence in our ability to make a difference.
To view the complete code for our project and the documentation, you can visit our GitHub repository here :
the model repo
the main repo
The repository contains everything needed to understand and reproduce our system, including preprocessing scripts, model training, and prediction functions.
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