A production voice agent has a latency budget of roughly 800 milliseconds before a conversation starts to feel slow. That budget is spent across eight sequential stages, typically split across three to five different vendors depending on how the stack is assembled. This post maps that voice
Once again, WebRTC Live broadcasted direct from the RTC.ON conference in Kraków, Poland where WebRTC.ventures CTO Alberto Gonzalez interviewed two speakers: And one guest: WebRTC Live #117: Live from RTC.ON 2026 Episode highlights below the video. Episode Highlights Pratim Mallick, Staff Software Engineer at Stream Charles Duyk,
The most frustrating thing about speaking with a Voice AI agent is when it interrupts you, or it doesn’t understand the normal flow of human conversation. There are multiple ways to solve this depending on your use case, and coming up with the best architecture for your
Self-hosting a voice AI pipeline gives you control that managed APIs can’t offer: you choose the models, you decide where they run relative to each other, and you keep audio data within your own infrastructure. Getting there means managing GPU workloads, model placement, and service networking yourself.
