Eliminate drop-out and protect university budget. AI that retains your students.
Improve student experience and student retention. CampusFaro is an ML-powered early warning system giving your staff ready-to-use rescue recommendations.
BACKED BY PREMIER EDTECH ACCELERATORS
Why current methods fail.
You find out about problems at the end of the semester. The decision to leave is already made. Your staff is handed a departure form—even though it could have been prevented.
Leaky Bucket
Every lost student is thousands of euros lost from tuition or state subsidies. A massive hit to your financial predictability.
Too Late to React
You find out when the student submits a departure form—even though this loss could have been easily prevented.
Overwhelmed Staff
Dozens of disconnected spreadsheets. Your advisors have no time for authentic, empathetic support.
From reactive firefighting to proactive retention
Give your team the exact insights they need, exactly when they need them.
Before CampusFaro
- Reactive firefighting
- Loss of subsidies and tuition
- Frustrated and overworked staff
With CampusFaro
- Proactive retention and student care
- Secured finances and predictable budget
- Time reclaimed for the student
Measurable financial and operational impact
Retaining just 100 students a year protects over €300,000 in your financial streams.
+5% retention lift in early deployments. More enrolled students, secured funding.
Detect risk signals before a student makes the emotional decision to leave.
Staff focus only on high-impact interventions with clear next steps.
How to save a student in 3 steps
No clunky software. Just clear actions.
Early Detection
We analyze attendance, grades, and engagement to flag risk weeks in advance.
Next Best Action
Your staff receives a precise action prompt. The system supports fully automatic and semi-automatic interventions.
Secured Retention
The student gets support. You secure engagement and funding.
3 Pillars of Support Powered by AI
Payment Issues (Protecting Tuition)
The system identifies payment delays. Instead of sending cold reminders, it suggests supportive interventions like installments or stipends, saving the student and the budget.
Academic Difficulties (Academic Shock)
Analyzing grades and attendance, AI detects students falling behind before they fail exams. Staff is prompted to offer mentoring.
Motivation & Student Experience
ML models catch subtle drops in digital activity. Your team steps in with an empathetic conversation when the student needs it most.
Explore a Pilot Programme
Test our early detection on a subset of your students before full deployment.
Duration
6–8 weeks
Scope
Selected student group or programme
Outcomes
- Identify at-risk students early
- Test intervention workflows
- Measure the direct impact
See how this would work at your university
Book a 20-minute conversation to explore a pilot. See why institutions with large student populations trust our 20 years of experience.