# Amazon — Building ultra-low-latency voice AI applications on AWS

- Company: Amazon (amazon.com)
- Announced: 2026-11-03T16:40:54+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/building-ultra-low-latency-voice-ai-applications-on-aws/
- Record: https://forck.live/items/31096-building-ultra-low-latency-voice-ai-applications-on-aws
- Subject: Bedrock / Nova
- Models affected: Sonic, Ink

Amazon's post explains how Cartesia, an AWS Partner, uses State Space Models and AWS infrastructure to run real-time voice AI with sub-100ms text-to-speech and speech-to-text. Cartesia's two production models are Sonic for speech generation and Ink for transcription, both built on State Space Model architecture rather than the transformer attention mechanism. Transformers process entire sequences before producing output, so higher quality often means higher latency, while SSMs carry a compact internal state forward and process input token by token. Sonic returns a first audio byte in approximately 90ms, supports over 44 languages, and can clone a voice from 10-second audio samples. Ink adds native turn detection, context-aware end pointing, streaming partial transcripts, noise robustness and multi-speaker support, so a downstream LLM can start forming a response before the speaker's turn ends.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/building-ultra-low-latency-voice-ai-applications-on-aws/:

> Conversational AI is transforming how humans interact with technology. From virtual assistants and AI-powered contact centers to real-time translation and accessibility tools, voice-first interfaces are rapidly becoming the default mode of interaction for millions of users worldwide.
> 
> Yet delivering a truly natural voice experience remains one of the hardest challenges in AI infrastructure. Users expect human-like responsiveness. Excess latency can break conversational flow and erode trust. To feel natural, AI-generated speech must arrive within the same temporal window as human turn-taking.
> 
> This post introduces how Cartesia , an AWS Partner specializing in real-time voice AI, uses purpose-built State Space Models (SSMs) and AWS infrastructure to deliver sub-100ms text-to-speech and speech-to-text at global scale. Developers can build voice experiences that feel indistinguishable from human conversation.
> 
> The rise of conversational AI and latency expectations
> 
> The demand for real-time voice AI is growing rapidly across industries:
> 
> Contact centers: AI agents handling millions of customer interactions require instantaneous speech generation to maintain natural dialogue.

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