The Challenge
Every admission season, the institute's 4 branches saw enquiry volume spike sharply for a 3-week window — historically requiring 3–4 temporary front-office hires per season just to keep up with calls, most of whom were barely trained before the rush ended. Outside admission season, front-office staff also spent significant time on fee-reminder calls, a task most found uncomfortable and often deprioritized.
The Solution
Voni AI was deployed across all 4 branches with a shared but branch-configurable call flow:
1. Admission Enquiry Handling — Every inbound enquiry (walk-in follow-up numbers, Google ads, referrals) was answered instantly, walking parents/students through batch options, fee structure, and timings, and booking a counselling slot for serious enquiries. 2. Fee Reminder Calling — Automated, consistently-toned reminder calls went out on a fixed monthly schedule, with a payment link sent by email immediately after each call. 3. Batch and Schedule Information — Routine schedule queries were handled automatically, freeing staff from repetitive information calls.
Implementation Timeline
All 4 branches were configured and live within 10 days, well ahead of the following admission season.
The Results
- 500+ admission enquiries handled across the 3-week peak season without any temporary hiring.
- Fee collection cycle time reduced, with more parents paying within the first reminder cycle rather than requiring repeated manual follow-up.
- Front-office staff redirected from repetitive calling to in-person counselling and enrollment conversations — the higher-value part of their role.
In Their Words
"Admission season used to mean chaos and temporary staff we didn't have time to train properly. This year, Voni AI handled the volume and our own team focused on actually counselling students." — Director, Sajag Institute
Why It Worked
Because the use-case (admission enquiries and fee reminders) is highly repetitive and predictable, automation delivered consistent quality at peak volume — exactly when a stretched, partially-trained seasonal team would have struggled most.
