Multilingual voice AI agents for Indian businesses
The short answer
A multilingual voice agent answers and places calls in Indian languages, holds a natural turn-taking conversation, acts in your backend systems and transfers to a person when it should. Branemind builds these for code-switched speech, measured on latency and containment against a baseline captured before go-live.
The call centre is the bottleneck, and the language list keeps growing
Call volume is spiky, staffing is not, and abandonment climbs at exactly the hours that matter. Adding languages multiplies the problem, because a Hindi-only script fails the caller who starts in Hindi and finishes in English, which is most callers.
What it costs today
- Abandoned calls at peak, which arrive again as complaints
- Language coverage that depends on who happens to be on shift
- Repetitive calls, order status and appointment changes, consuming trained agents
- No usable record of what was said, so disputes are unresolvable
What we build, and where we stop
The second list matters as much as the first. A boundary that is agreed in writing before the build is the difference between a system your compliance team signs off and one they discover.
What we build
- Inbound and outbound call flows with natural turn-taking and barge-in
- Speech handling tuned for Indian languages and code-switching
- Backend actions during the call, so the caller does not repeat themselves
- Warm transfer to a human with the context already passed
- Live transcripts, recordings and CRM sync
- A latency budget defined and monitored per stage of the pipeline
What we do not do
- Pretend to be a human. The agent identifies itself as an assistant
- Handle a distressed or hardship call to conclusion. Those transfer
- Record without the disclosure your jurisdiction requires
- Promise a language we have not evaluated on your own call recordings
How it works
- 01
Detect language, then stop switching
The agent settles on the caller's dominant language quickly and holds it, while still understanding code-switched input. Constant switching is more disorienting than a slight accent mismatch.
- 02
Budget the latency, stage by stage
Speech recognition, model response and speech synthesis each get a share of the budget. Latency is measured end to end from end-of-speech to start-of-audio, because that is what the caller experiences.
- 03
Act mid-call
Order lookups, appointment changes and payment links happen during the call through your APIs, and the agent confirms only what came back.
- 04
Transfer warm
On escalation the human receives the transcript and the caller's intent, so the caller does not start again.
- 05
Evaluate on your own recordings
Before go-live, the pipeline is evaluated against a sample of your real calls, not a vendor demo set.
What it connects to
- Telephony providers and SIP trunks
- Speech recognition and synthesis providers, including Indian-language models
- CRM and ticketing systems
- Order, booking and billing backends
- Call recording and storage
What you need in place
We would rather tell you this before a proposal than during one.
- A sample of real call recordings for evaluation, with consent to use them
- A defined language list, in priority order
- A staffed transfer destination during published hours
- Agreement on recording disclosure wording
Controls, approvals and what happens when it fails
Disclosure
The agent states that it is an automated assistant at the start of the call, and the recording disclosure is played where required.
Escalation triggers
Explicit request, distress or hardship signals, repeated recognition failure and any reserved topic transfer to a person.
Latency monitoring
Per-stage latency is monitored in production, since a regression in one provider degrades the whole call.
Transcript retention
Transcripts and recordings are retained under your policy and are available for dispute resolution.
The proof
A voice agent that holds its own in nine Indian languages
Support in English served maybe a third of the callers. Sovereign Indic models and a hard latency budget served the rest, including the ones who switch language mid-sentence.
- p95 latency
- 320ms
- Containment
- 63%
- resolved without a human
- Languages live
- 9
What we measure, and what we do not promise
- What we measure
- End-of-speech to start-of-audio latency at the median and the tail, containment rate, transfer rate and reason, recognition accuracy per language, and caller-reported resolution.
- What one engagement measured
- The consumer services case study covers nine Indian languages with its latency and containment figures stated against a defined measurement method. Read the method before comparing it with a vendor benchmark.
- Where voice is the wrong answer
- Long form-filling, anything needing a document, and emotionally loaded conversations. We will say so rather than build it.
What this ships on
Questions we get asked
How do multilingual voice agents handle Hindi-English code-switching?
By treating the mixed utterance as normal rather than as an error. The recognition layer has to be trained or configured for code-switched speech, and the agent settles on one output language rather than mirroring every switch, which is what callers report as most natural.
What latency is acceptable on a voice agent?
What matters is the gap between the caller finishing a sentence and hearing a response begin. Under roughly a second feels conversational, and beyond about two seconds callers start talking over the agent. Any figure quoted without saying where it was measured is not comparable.
How many Indian languages can you support?
The honest answer depends on your call mix. We evaluate candidate languages against a sample of your own recordings and report accuracy per language, rather than publishing a language count that has not been tested on your traffic.
Does the agent say it is an AI?
Yes. It identifies itself as an automated assistant at the start of the call. Beyond the regulatory position, callers who know they are talking to a machine speak in ways that work better.
Test one multilingual call flow
We evaluate one real flow against your own recordings.