A Voice agent in hindi that answers customer support calls with no
human intervention
A production voice agent automating inbound customer support for Battery
Smart, India's largest EV battery swapping network - it speaks Hindi,
pulls live data from database, battery, and station APIs and resolves
in scope calls end-to-end with zero human handoff.
Battery Smart operates India's largest EV battery-swapping network.
Its users are drivers on the road all day, Hindi-speaking and
phone first. When a driver needs to know their battery status, find
the nearest station with available batteries or check a payment, they
call.
That made the call centre the operational bottleneck: every new cohort
of drivers added call volume and the only way to absorb it was more
headcount.
The Problem
Support costs scaled linearly with growth
Most inbound calls were repetitive, structured lookups, battery
status, station availability, swap history, account and payment
queries; consuming trained agents on work a system could do.
Peak hour queues left drivers waiting at swap stations for answers
they needed immediately.
The caller base is Hindi first. Conventional IVR menus and
English centric bots performed poorly and drove calls straight back
to human agents.
24/7 coverage meant night shifts and redundancy, expensive to
staff, hard to retain.
The Solution
A voice agent wired into live production data
We built a Hindi voice agent that answers the call, understands the
request, fetches the answer from live systems, and speaks it back in a
full conversation loop with no human in it.
Hindi native speech pipeline. Sarvam AI STT/TTS
tuned for Hindi and Hinglish code switching, robust to noisy
roadside audio.
Real answers, not scripts. The LLM agent layer
calls production APIs at answer time with battery state, station
availability and account data are live, never canned.
Hard scope guardrails. The agent resolves in-scope
queries end-to-end and gracefully hands anything else to the
escalation path; it doesn't guess.
Conversational latency. A streaming STT/TTS
pipeline keeps response times natural: ~200ms latency on average.
Results
Support capacity decoupled from headcount
In scope driver queries no longer touch a human. The call centre
workforce is reserved for genuinely complex cases; support capacity
stopped scaling with customer growth.
ZeroHuman handoff for in scope queries resolved fully by the
agent
1000+Inbound calls handled per month
70%Share of total inbound volume automated
30%Reduction in call-centre workforce dependency
24/7Coverage — nights and holidays included, no shift staffing
+70%First-call resolution rate for in-scope queries
Tech Stack
What it's built with
Sarvam AI STTSarvam AI TTSLLM Agent Layer — Tool CallingLive REST API IntegrationsTwilioMeta Llama 3.3 70B
Support volume scaling faster than your team?
We'll show you a live voice agent on the call and map out what
automating your inbound support would look like.