25-40% of college students and 50%+ of online students drop out. Each dropout costs institutions $8K-20K in lost revenue.
Predict student dropout risk and enable targeted retention interventions
Identify at-risk students early by correlating engagement, grades, attendance, and financial-aid data. Agents surface actionable insights for advisors and generate intervention recommendations.
18%improvement in student graduation rate
42%of at-risk students successfully retained with intervention
60 daysaverage early warning lead time before dropout
$3.2Mannual tuition revenue retained (per 5K student cohort)
.// The Challenge
The challenge
Universities and online schools lose 25-40% of students before completion. Dropout risk signals (poor grades, low engagement, financial stress) are identified too late for intervention. Student success teams lack proactive insights into who’s at risk. Intervention resources are allocated reactively, not strategically. Early warning systems exist but are hard to use; actionable insight is limited. Retention efforts are generic; interventions aren’t personalized.
.// The Solution
How assistents solves it
assistents student success analyst connects to your LMS, SIS, and student engagement platforms to predict dropout risk. The agent identifies at-risk students by analyzing engagement (login frequency, assignment submission), academic performance (GPA trend, course pass rates), and financial status. High-risk students are flagged for targeted intervention: tutoring referral, financial counseling, mentor matching. The agent recommends intervention type based on student risk profile. Follow-up engagement is tracked to measure intervention effectiveness.
Data Analyst Agent
Reads LMS and SIS data, calculates engagement and academic metrics, predicts dropout risk
Active
Conversational Agent
Reaches out to at-risk students, offers support, directs to resources
Active
Workflow Agent
Triggers intervention alerts, matches students to mentors/tutors, tracks engagement post-intervention
Active
.// How It Works
How it works
Connect student data
LMS, SIS, and student engagement platforms are integrated. Agent accesses student data continuously.
Calculate risk scores
Agent analyzes GPA trends, assignment submission, login frequency, and financial status.
Predict at-risk students
ML model predicts dropout probability. Students with >40% risk are flagged for intervention.
Reach out & offer help
Agent contacts student, offers support (tutoring, financial help, mentoring). Schedules follow-up.
Track & improve
Agent tracks student re-engagement post-intervention. Measures which interventions work best.
.// Measurable Outcomes
Measurable outcomes
improvement in student graduation rate18%
of at-risk students successfully retained with intervention42%
average early warning lead time before dropout60 days
annual tuition revenue retained (per 5K student cohort)$3.2M
.// Get Started
Ready to see this in action?
Schedule a personalized demo to see how assistents’s AI agents can solve this challenge for your organization.