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

> **Publication**: aitalky (Independent AI Journalism)
> **Canonical Citation URL**: https://aitalky.vercel.app/news/building-ultra-low-latency-voice-ai-applications-on-aws
> **Original Source**: [AWS ML Blog](https://aws.amazon.com/blogs/machine-learning/building-ultra-low-latency-voice-ai-applications-on-aws/)
> **Author**: Nolan Chen (undefined)
> **Published Date**: Tuesday, November 3, 2026
> **Category**: INDUSTRY
> **Tags**: AI, AWS ML Blog, industry

## Executive Summary
Learn how Cartesia, an AWS Partner, uses purpose-built State Space Models and AWS infrastructure to deliver sub-100ms text-to-speech and speech-to-text at global scale, and how to deploy its Sonic model on Amazon SageMaker AI or self-managed Amazon EC2 GPU...



## Full Coverage
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

---
*Generated for AI agents and LLM citation by aitalky (https://aitalky.vercel.app).*