Education Technology
Voice AI for EdTech: Multilingual Outbound at Scale.
Context, Not Cold Scripts.
TL;DR: EdTech outbound calling in India hits a wall that generic dialers cannot solve. Students and parents expect conversations in their own language, and a single script does not work across career guidance, parent-teacher follow-up, enrollment, feedback, and re-engagement. Kathan Voice OS handles all of these natively across 12+ Indian languages, with retargeted cohorts consistently outperforming cold outreach because context accumulates across attempts.
The Problem: Multilingual Outbound at Scale Breaks Generic Dialers
EdTech operations in India span career guidance for new prospects, parent-teacher follow-ups for existing students, enrollment for upcoming batches, feedback collection, and re-engagement of leads who went cold. Each motion has its own opening, tone, and decision logic, and most run across at least four languages. Traditional manual dialing requires a large, expensive team. Generic AI dialers achieve 20 to 25% connection rates and treat every retry like a cold call, so retargeted leads convert worse than fresh ones, the inverse of what should happen when the institute already has prior signal on the lead.
“EdTech operations in India span career guidance for new prospects, parent-teacher follow-ups for existing students, enrollment for upcoming batches, feedback collection, and re-engagement of leads who went cold. Each motion has its own opening, tone, and decision logic, and most run across at least four languages. Traditional manual dialing requires a large, expensive team. Generic AI dialers achieve 20 to 25% connection rates and treat every retry like a cold call, so retargeted leads convert worse than fresh ones, the inverse of what should happen when the institute already has prior signal on the lead.”
The Solution: Voice Agents That Carry Context Across Attempts
Kathan does not work from a flat script. Each call carries a live, filtered view of the lead's history, the campaign's objective, the language preference, and the prior interaction trail. A retargeted Gujarati parent receiving a third PTM follow-up call hears a conversation that references the prior objection, the specific student, and the upcoming event by name, in Gujarati from the first syllable. The agent calling a Telugu CA student about exam prep operates from a different context entirely.
Six to twelve languages handled natively per deployment, with regional phrasing rather than English scripts dubbed through TTS.
Per-campaign behaviour tuning so career guidance, PTM, enrollment, feedback, and retargeting each follow their own conversational logic.
Persistent context across attempts
retargeted leads are not called from zero, and connection compounds across waves.
TRAI-compliant caller ID, time-window enforcement, and complete audit trails.
Where It Fits in the Student Lifecycle
Five workflow patterns repeat across coaching institutes, online platforms, and certification academies. Each one absorbs counsellor or admin bandwidth that should be focused on the high-intent conversations only humans can have.
Career Guidance Outreach
first-touch conversations with new prospects in their preferred language, qualifying interest before a counsellor ever joins.
Parent-Teacher Follow-Ups
reminders and rescheduling for PTM events, with parent-language conversations that respect regional norms.
Course Enrollment Drives
outbound calls during open windows that reference the specific course and prior interactions.
Feedback & NPS Collection
post-batch and post-event feedback at multiples of email response rates.
Lapsed-Lead Re-Engagement
retargeting waves that consistently outperform cold outreach because the agent already knows the lead's prior objection.
Why It Works for EdTech Specifically
Education is a relationship business, and the relationship is rarely English-only. A Gujarati parent expects a Gujarati conversation, and the call is lost in the first ten seconds otherwise. The compounding effect of context across attempts is also more visible in EdTech than almost any other vertical: by the third touch, a retargeted cohort can connect at 1.5x the cold-outreach rate because every prior interaction sharpens what the agent says next. The result is an outbound motion that actually scales without scaling the headcount behind it.
“Education is a relationship business, and the relationship is rarely English-only. A Gujarati parent expects a Gujarati conversation, and the call is lost in the first ten seconds otherwise. The compounding effect of context across attempts is also more visible in EdTech than almost any other vertical: by the third touch, a retargeted cohort can connect at 1.5x the cold-outreach rate because every prior interaction sharpens what the agent says next. The result is an outbound motion that actually scales without scaling the headcount behind it.”
A Customer Putting This to Work.
Named deployments and scoped engagements where this exact set of workflows runs against real patient, student, customer, or member data.
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