How the app works Demo

Live Demo

In South Africa, over 60% of the population lives below the poverty line (World Bank, 2022). This socio-economic reality directly impacts access to higher education.

Every year, thousands of students face a registration crisis: they cannot pay the upfront registration fees required to secure a place at university. This leads to:

• Long queues at campuses as students appeal for fee exemptions.
• Stress and uncertainty for students and their families.
• Administrative burden for tertiary institutions, who face protests and delays.
• Donors and funding bodies struggling with late applications, unclear priorities, and bottlenecks in distributing aid.

Financial exclusion remains a leading cause of student dropout, with delayed funding from schemes like NSFAS leaving many unable to continue studies.

Imagine a seamless registration season where:

• Students apply online for help with registration fees and are instantly matched with donors.
• Donors (alumni, corporates, NGOs) receive AI-curated student profiles and can fund students in real time.
• Universities drastically reduce queues, protests, and admin stress.
• Students start the semester without financial anxiety, focusing on academics.

This transforms registration from chaos into a data-driven, AI-powered funding ecosystem.

We are building an AI-driven micro-bursary and peer-to-peer funding platform, integrated with a student banking system.

• Students register with academic, socio-economic, and course details.
• They can request specific support for registration fees, tuition, or living costs.
• Donors/alumni/corporates set funding preferences (field of study, GPA thresholds, type of support).
• AI algorithms match students with donors based on financial need, academic trajectory, and donor intent.
• Funds are disbursed instantly into student bank accounts, ensuring they can register and stay enrolled.

• Early detection of students at risk of missing registration due to unpaid fees.
• AI identifies donor-student alignment, increasing donor satisfaction and impact.
• Universities gain predictive insights into registration bottlenecks.
• Students access financial literacy tools via their digital bank account.

• AI-Powered Matching Engine – Matches donors to students at the exact point of need.
• Micro-Bursary Model – Splits donor contributions into bite-sized bursaries to clear registration blocks.
• Registration Fee Priority Feature – Fast-tracks urgent cases to prevent dropouts.
• Digital Queue Reduction – Automates bursary allocation, reducing campus queues and protests.
• Impact Dashboards – Real-time donor impact tracking.
• Financial Wellbeing Layer – Budgeting and savings tools for students.

• Django Backend – Handles authentication, bursary requests, donor profiles, and AI match logic.

• Machine Learning Layer – A trained model (Random Forest / Recommendation System) predicts donor-student matching scores.

• REST API – Exposes matching scores, bursary status, registration alerts, and transaction history.

• Frontend – HTML/CSS templates with:

  • Student dashboard (apply for bursaries, see match score)
  • Donor dashboard (view students, fund with 1 click, view impact dashboard)
  • Wallet simulation (mock transactions, disbursement updates)
  • Academic record uploads and registration status flags

• ✅ Student & donor registration
• ✅ Bursary request creation
• ✅ AI-powered donor-student matching
• ✅ Donor funding (mock payments)
• ✅ Academic record upload
• ✅ Real-time queue reduction insights for universities
• ✅ Alerts for at-risk students

• Backend: Django, Django REST Framework
• ML Model: Scikit-learn (RandomForest / Logistic Regression)
• Database: SQLite (can scale to PostgreSQL)
• Frontend: HTML, CSS, JS (Bootstrap or Tailwind)
• Payments: Mock payment API integration

1. Clone the repo

git clone https://github.com/Simacoder/FundForward.git
cd FundForward

2. Install dependencies

pip install -r requirements.txt

3. Run migrations & server

python manage.py migrate
python manage.py runserver

4. Access app: http://127.0.0.1:8000

• ✅ Mobile app for students
• ✅ Integration with real payment gateways
• ✅ Machine Learning model optimization with real data
• ✅ Predictive dropout alerts for university admins

MIT License – free to use, modify, and distribute.

• Simanga Mchunu
• Yusairah Ismail
• Patience Mabuza
• Nkosinathi Nhlapo