Student Success AI Across 62,000 Enrolled Students
Illustrative reference architecture. This is a composite engagement template built to show how Mopshy structures enterprise work. It is not a real Mopshy client, and every figure, KPI, and quotation on this page is illustrative rather than measured client data.
Predictive advising, AI writing feedback, and 24/7 support agent across four campuses — FERPA-aligned and faculty-governed.
+11 pts
First-year retention
62%
Tier-1 tickets self-served
3×
At-risk student interventions
The bottleneck
First-year retention had drifted below 78%. Advising ratios exceeded 1:400. Late-night support demand outstripped a fully in-person help desk.
The system
- Retention-risk model flagging early-warning signals from LMS + SIS
- AI writing feedback embedded in Canvas with instructor guardrails
- 24/7 conversational support agent triaging tier-1 questions across financial aid, registrar, and IT
- Faculty governance council reviewing model use quarterly
Outcomes measured, not promised
62K
Students served
88%
Advisor satisfaction w/ risk model
−34%
Time to first advising touch
0
FERPA incidents
What it cost, what it returned
Investment
$2.9M program (year one)
Payback
12 months
Annualized value
$21M retained-tuition value
Value tied to institutional retention-per-point tuition contribution model.
How it is built
- Data platform unifying SIS, LMS, and advising notes
- Retention-risk model with campus-specific calibration
- AI writing feedback with prompt allowlists and instructor overrides
- Support agent with escalation to human within one turn
Representative engagement. This case study describes a composite of Mopshy AI's enterprise engagement patterns, delivery methodology, and observed outcome ranges. Company names, individual quotes, and specific figures are illustrative and used to communicate the enterprise pattern rather than to describe a single identified client.
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