Announcing our Series A Funding

Announcing our Series A Funding

AI Voices for Voice Chatbots

Web chat is unusual because the visitor reads and listens at once. These voices suit an unhurried delivery, begin playing in about 200 milliseconds over WebSocket, and cover twelve languages from one integration.

VOICES FOR THIS USE CASE

Nicolasnicolas
MaleYoungFrench
Best for FrenchUse voice
Barathbarath
MaleYoungIndian
Best for HindiUse voice
Femkefemke
FemaleYoungDutch
Best for DutchUse voice
Jasleenjasleen
FemaleYoungIndian
Best for HindiUse voice
Tamilselvitamilselvi
FemaleYoungIndian
Best for HindiUse voice
Kevalkeval
MaleYoungIndian
Best for HindiUse voice

Why chat is harder than narration

A narrator can be a second late and nobody notices. A chatbot cannot. Replies have to begin inside the pause a person expects in conversation, which means streaming rather than waiting for a complete file. Audio starts in about 200 milliseconds on the streaming endpoints, which is inside that window.

Handling a multilingual audience

Voices in the Indic family cover eleven Indic languages plus English, so one voice can answer a Hindi visitor and a Tamil visitor without re-casting. Switching the language parameter carries no latency penalty. The boundary is the European family, which those voices do not reach.

Voices that suit reading along

Web chat is unusual in that the visitor often reads the text while hearing it. That favours an unhurried delivery over an animated one, since the two channels compete for attention. 195 voices carry the conversational tag, which is the broadest group in the catalog and the right place to start casting.

Caching the predictable parts

Most chatbot output is repetitive. Greetings, confirmations and closings recur across nearly every session, and generating them repeatedly is wasted. Hashing the text and caching the audio removes most of the recurring cost, and it also makes those common replies instant rather than merely fast.

SPECIFICATION

Sample rate

44.1 kHz native, resampled to 8 kHz for telephony

Latency

~200 ms to first byte (p50, warm region)

Output formats

ulaw, alaw, PCM 16-bit, WAV, MP3

Streaming transports

WebSocket, HTTP chunked transfer

Speed range

0.5× – 2.0×, set per request

Explore Voice Similar to

AI Voices for Voice Chatbots

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Multilingual & Code-Switching AI Voices

Seventy two voices cover eleven Indic languages plus English, so one voice serves a Hindi caller and a Tamil caller without re-casting. Hindi and English can alternate inside a single sentence.

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At volume the cost driver is duplication, not generation. Hashing text and skipping what already exists removes most of it, since catalog and template work repeats the same phrases constantly.

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Voice agents live or die on the pause before a reply. Synthesis starts in about 200 milliseconds and runs at 3.3 times real time, which leaves the budget where it usually belongs: your model.

AI Voices for Customer Support Automation

Support calls reach people who are already inconvenienced, often on a poor line. These voices favour clarity over character, hold steady across renders, and move between Hindi and English the way callers actually do.

AI Voices for IVR & Telephony

IVR voices need to survive a compressed phone line, not just sound good in a browser. These output ulaw and alaw directly, generate in roughly 200 milliseconds, and handle Hindi and English in the same prompt.

Conversational Voices

One hundred and ninety five voices carry the conversational tag, 84 percent of the catalog. Streaming is what makes them feel live: audio begins playing before the sentence has finished rendering.

Friendly Voices

For Indian customer facing work the deciding factor is not tone but language. These voices switch between Hindi and English mid sentence, which reads as considerably more natural than either alone.

Multilingual & Code-Switching AI Voices

Seventy two voices cover eleven Indic languages plus English, so one voice serves a Hindi caller and a Tamil caller without re-casting. Hindi and English can alternate inside a single sentence.

AI Voices for Live Narration & Streaming

Generation runs at 3.3 times real time, so audio renders faster than it plays and the buffer stays ahead. First audio arrives in about 200 milliseconds over SSE or WebSocket.

AI Voices for Batch Voiceover Pipelines

At volume the cost driver is duplication, not generation. Hashing text and skipping what already exists removes most of it, since catalog and template work repeats the same phrases constantly.

FAQs

It is a voice interface that responds inside the pause a person expects in conversation, rather than after a visible wait. That needs streaming rather than batch generation, so audio begins playing before the full sentence is rendered. Both SSE and WebSocket transports are available for this.