VoicEra — everything you need to know.

VoicEra is a platform that lets you build and deploy AI voice agents that can have real phone conversations — in Indian languages.

Think of it like this:

Someone calls a phone number. An AI picks up. They have a full conversation in Hindi, Kannada, Tamil, Telugu — whatever language the caller speaks. The AI understands them, thinks, and responds — all in under 2 seconds.

That's VoicEra.

India has 1.4 billion people. The vast majority don't speak English as their first language.

Every major voice AI platform in the world — Raya, Ring, Vapi, Bland — was built in the West. For English speakers. On American servers. Closed source. Expensive.

There was no production-grade voice AI platform built for Indian languages. No open source option. No on-premise option. Nothing affordable for Indian scale.

VoicEra fills that gap.

There are five things that make VoicEra unlike anything else:

1. 1

   Open Source

   The entire platform is open source. Every line of code is public. Anyone can download it, deploy it, modify it, and contribute to it. No other voice AI platform has done this.

2. 2

   Built for Indian Languages

   VoicEra is natively built for Indic languages using AI4Bharat's speech models and BHASHINI's language APIs — two of the most serious Indian language AI initiatives in the country. It doesn't treat Indian languages as an afterthought.

3. 3

   On-Premise Option

   You can run VoicEra entirely on your own servers — no cloud dependency, no data leaving your building. This is critical for banks, hospitals, government bodies, and any organisation with data privacy requirements.

4. 4

   Extremely Affordable

   ₹0.28 per 2.5-minute call. That's it. Compared to Western platforms that charge many times more, VoicEra makes voice AI economically viable for India-scale deployments.

5. 5

   Production Grade

   This isn't a prototype or a research project. VoicEra is engineered to handle 50 simultaneous phone calls on a single machine, with responses in under 2 seconds.

Every time someone makes a call through VoicEra, here's what happens — in sequence, in under 2 seconds:

Person speaks on the phone
        ↓
Voice is captured (Telephony)
        ↓
Speech is converted to text (STT — Speech to Text)
        ↓
Text is sent to an AI model (LLM — the brain)
        ↓
AI generates a response in text
        ↓
Text is converted back to voice (TTS — Text to Speech)
        ↓
Voice is played back to the caller

This entire loop — from the person finishing their sentence to hearing the AI respond — takes less than 2 seconds.

STT — Speech to Text

This is the part that listens to what someone says and converts it into text the AI can understand. VoicEra uses AI4Bharat's STT models — trained specifically on Indian languages and accents. It can handle fast speech, accented speech, noisy phone audio, and mixed language sentences.

TTS — Text to Speech

This is the part that takes the AI's text response and converts it into a natural-sounding voice. Again, VoicEra uses AI4Bharat's TTS models — so the voice sounds natural in Hindi, Kannada, Tamil, Telugu, and other Indian languages.

Both STT and TTS are optimised to run on a single GPU server, handling 50 calls simultaneously without degrading in quality or speed.

The orchestration layer is the brain of VoicEra. It's the part that coordinates everything.

When a call comes in, the orchestration layer:

• Starts and manages the call
• Routes the audio to the right STT service
• Sends the transcript to the AI model
• Takes the AI's response to the TTS service
• Plays the audio back to the caller
• Logs everything — transcript, recording, summary
• Handles errors and retries if anything fails
• Manages multiple calls happening at the same time

Think of it as the conductor of an orchestra. Every instrument (STT, LLM, TTS, telephony) plays its part — the orchestration layer makes sure they all play together in perfect time.

VoicEra can be deployed in two ways depending on what an organisation needs:

Any organisation can use VoicEra to build voice agents for their use case. Some examples:

Any use case that today requires a human call-centre agent speaking in a regional language — VoicEra can handle it.

VoicEra is a complete platform, not just an API. It includes:

For those who want to know what it's built on:

Everything runs in Docker containers — making it straightforward to deploy on any infrastructure, on-premise or cloud.

These are not theoretical targets. The platform is engineered to hit these numbers consistently.

On a single cloud instance handling 50 concurrent calls:

The cost per call stays flat at ₹0.28 regardless of scale.

VoicEra is relevant for anyone who needs to communicate with Indian citizens at scale, in their language, over a phone call.

• Government bodies and civic tech organisations — citizen services, public health, awareness campaigns
• BFSI (Banking, Financial Services, Insurance) — customer service, collections, onboarding
• Healthcare — appointment booking, health advisory, medication reminders
• Agritech — farmer advisory services
• Developers and researchers — build on top of the open source platform
• Any organisation that currently runs a regional-language call centre

Three things are converging right now:

1. 1

   The models exist.

   AI4Bharat has built world-class speech models for Indian languages. BHASHINI is India's national language technology platform. The AI is ready.

2. 2

   The infrastructure exists.

   GPU servers, cloud computing, telephony APIs — all available in India at reasonable cost.

3. 3

   The platform layer was missing.

   No one had built the open, production-grade middleware that connects all of this into a deployable voice AI system.

VoicEra is that missing layer.

And because it's open source — it doesn't belong to any one company. It belongs to everyone who builds on it, contributes to it, and deploys it.