Rungta Colleges (SRGI Bhilai)
Client Snapshot
Sanjay Rungta Group of InstitutionsEdTech / Higher Education — Bhilai, ChhattisgarhSize: 500
Sanjay Rungta Group of Institutions (Rungta Colleges) is a multi-campus engineering, pharmacy, management and ITI education group headquartered in Bhilai, Chhattisgarh, covering RCST, RISM, RIPS, RIPSR, RPITI and RSR-RCET. Programs span B.Tech, BBA, BCA, BCom, B.Sc, B.Ed, DCA, B.Pharma, D.Pharma, M.Pharma, ITI trades, MBA, MCA, M.Tech and PhD, with partner MoUs including Cisco Academy, Microsoft and IIT Roorkee. Admission cycles drive heavy inbound enquiry volume from students, parents and lateral-entry aspirants in tier-2 and tier-3 markets.
Caller Digital’s Conversational AI
Caller Digital deployed an outbound voice AI agent aligned to Rungta's existing English + Hindi Common Counselling Script (Career Selling → Course Selling → Why SRGI → Call to Action). The agent handles three personas — Class-12 students, tier-2/3 parents, and diploma / lateral-entry aspirants — with Hinglish-first conversation that mirrors the lead's preferred mode. Across eleven core use cases (lead introduction & verification, course discovery, budget capture, eligibility pre-check, KB query answering, facility queries, objection handling, CTA, counsellor hand-off, voicemail handling, DND handling), the agent integrates with SRGI's CRM to push call summaries, transcripts, captured fields and dispositions. The knowledge base is grounded in Rungta course brochures, the Common Counselling Script and the Eligibility 2026–27 matrix. Hostel, transport, mess, library, gym, on-campus medical and safety queries are answered from the KB with honest 'I'll route to counsellor in 4 working hours' fallback for out-of-KB questions.
The deployment targets ≥55% connect rate, ≥70% qualification rate (course + budget + eligibility captured per connected call), ≥25% hot-lead conversion (qualified leads agreeing to campus visit / counsellor handover), ≥85% KB answer coverage (queries answered without escalation), ≥90% language-mirror accuracy (matching the lead's Hindi / English / Hinglish), 4.0+ post-call CSAT, and <4-working-hour counsellor hand-off SLA. Hinglish-first conversation aligned to the existing Counselling Script lets the voice AI co-exist with human counsellors without re-training the conversion funnel — qualified, hot leads land in the counsellor queue with full eligibility, budget, course interest and objection-history pre-captured, so counsellor time is invested only on closure rather than discovery.
The deployment targets ≥55% connect rate, ≥70% qualification rate (course + budget + eligibility captured per connected call), ≥25% hot-lead conversion (qualified leads agreeing to campus visit / counsellor handover), ≥85% KB answer coverage (queries answered without escalation), ≥90% language-mirror accuracy (matching the lead's Hindi / English / Hinglish), 4.0+ post-call CSAT, and <4-working-hour counsellor hand-off SLA. Hinglish-first conversation aligned to the existing Counselling Script lets the voice AI co-exist with human counsellors without re-training the conversion funnel — qualified, hot leads land in the counsellor queue with full eligibility, budget, course interest and objection-history pre-captured, so counsellor time is invested only on closure rather than discovery.
Before Caller Digital
Only a fraction of admission enquiries reached within 24 hours
Lateral-entry and working-aspirant calls relied on counsellor availability
Hostel, transport, mess, medical queries handled inconsistently by SDRs
MoU partnerships (Cisco, Microsoft, IIT Roorkee) discussed unevenly
Eligibility pre-checks done manually against a paper matrix
Evening, weekend and regional-time reachability limited by staff hours
After Caller Digital
100% of incoming admission enquiries called within 24 hours
Lateral-entry, working aspirant and parent personas all served via Hinglish AI
KB-grounded answers on hostel, transport, mess, medical, gym, safety
Cisco, Microsoft, IIT Roorkee MoUs cited consistently with placement narrative
Eligibility 2026–27 matrix applied per call with category-aware branching
9 AM–9 PM coverage across weekdays, weekends and regional time zones
Benefits of Integration
Read More Case Studies
Frequently Asked Questions
An outbound Hinglish-first voice AI agent for admission lead qualification across Rungta's multi-campus group (RCST, RISM, RIPS, RIPSR, RPITI, RSR-RCET), covering B.Tech, BBA, BCA, BCom, B.Sc, B.Pharma, D.Pharma, M.Pharma, ITI, MBA, MCA, M.Tech and PhD programs. The agent handles lead verification, course discovery, eligibility pre-check, KB-grounded query answering, objection handling and counsellor hand-off.
The agent mirrors Rungta's existing Common Counselling Script — Career Selling (rapport + interest generation), Course Selling (USPs + recruiters + fee band + eligibility check), Why SRGI (placement narrative + Cisco / Microsoft / IIT Roorkee MoUs + alumni stories), and Call to Action (campus visit booking, WhatsApp registration link, or senior counsellor callback). This alignment lets the AI co-exist with human counsellors without re-training the conversion funnel.
Hinglish-first by default, with natural code-switching between Hindi and English mirroring the lead's preferred mode. The agent handles three persona registers: tech-fluent Class-12 students (Hindi-English mid-sentence), tier-2/3 parents (Hindi-dominant, formal 'aap' / 'sir / madam'), and diploma / lateral-entry aspirants (Hindi with technical English terms).
The agent applies the Rungta Eligibility 2026–27 matrix per call: confirms qualifying exam (10+2 stream — PCM / PCB / PCMB / Commerce / Arts / Vocational), percentage, category (GEN / OBC / SC / ST / Handicap), and entrance exam where applicable (CG PET / JEE for B.Tech, PPHT for B.Pharma, CAT / CMAT / ATMA / XAT for MBA, NIMCET for MCA, GATE for M.Tech). Outcomes are tagged Eligible / Borderline / Not Eligible and surfaced to the counsellor in the structured pre-call brief.
≥55% connect rate, ≥70% qualification rate (course + budget + eligibility captured per connected call), ≥25% hot-lead conversion (qualified leads agreeing to campus visit or counsellor handover), 3–5 minute average handle time, ≥85% KB answer coverage, ≥90% language-mirror accuracy, 4.0+ post-call CSAT, and <4-working-hour counsellor hand-off SLA on AI-flagged hot leads.
Start Automating Calls Today
Unlock 24/7 multilingual AI voice agents for sales, support, & operations.
© 2025 Caller Digital | All Rights Reserved