Agentic CX for Indian-operator scale.
Indian telecom is a different game. Hundreds of millions of subscribers per operator. Conversations in 22 languages, often mixed mid-sentence. Margin per ARPU is single-digit rupees. The unit economics of customer-care automation are unforgiving — which is why Vihaya's CX engagements lead with measurable touchless-resolution rate, not Net Promoter score theatre.
Workflows we automate
Multilingual intent routing
Classify the customer's intent in any of 22 languages; route to the right resolution path with the agent's recommendation attached.
Billing-dispute review
Read complaint + bill + plan + usage logs → cited refund / deny / escalate. CSR sees the rec in their existing console.
Churn / retention intervention
Score churn risk against historical patterns; recommend a grounded retention offer with cited rationale.
Plan-change consultation
Read the customer's usage and recommend the plan that minimises spend — with the math shown.
Telecom FAQ
Which Indian languages does Vihaya CX support?
All 22 scheduled languages where there's reasonable foundation-model coverage — English, Hindi, Bengali, Tamil, Telugu, Marathi, Gujarati, Kannada, Malayalam, Punjabi, Odia, Assamese, and Urdu have strong day-one support. Mixed-language conversations (English-Hindi code-switch) work natively because the underlying models are trained on real Indian text.
Can this handle Jio / Airtel-scale volume?
Vihaya's stateless service tier scales horizontally. The bottleneck at India-operator volumes (10M+ interactions/day) is foundation-model rate limits and Postgres read throughput — both addressed by Azure OpenAI India / Vertex Mumbai provisioned capacity and Postgres read replicas. The pilot is typically scoped to one channel (one circle, one product) before extending.
How does the agent handle billing disputes?
The agent reads the customer's complaint (call transcript, chat, email), the disputed bill, the rate plan, and the usage logs. It produces a cited recommendation: refund / partial / deny / escalate. The customer-care agent sees the recommendation in their existing console; the audit row preserves the decision trail for TRAI compliance and internal QA.
What about TRAI compliance and customer-data regulations?
TRAI's customer-data norms and the DPDP Act both apply. Vihaya's audit trail records every action with purpose and outcome; PII redaction in logs is configurable. CDRs (call data records) stay inside the operator's environment — Vihaya is deployed in the operator's VPC and does not egress data.
Want to see this in your environment?
30-minute discovery call. Draft SOW within 5 business days.
Talk to us about a pilot →