Human speech is often unstructured and messy. To keep up with real conversation, Voice AI bots must parse partial sentences, filler words, and interruptions, all without the visual cues a human listener relies on. On top of that linguistic challenge, real-world latency budgets and network conditions test every Voice AI pipeline, and users don’t forgive one that stutters.
In this episode of WebRTC Live, host Arin Sime talks with Dr. Varun Singh, Chief Product Technology Officer at Daily.co / Pipecat.ai, about the engineering decisions that separate voice agents that succeed from ones that get abandoned. Topics include where Voice AI is working today and where it isn’t, from well-defined tasks like collections to the open-ended conversations everyone is still chasing, and how Pipecat approaches the problem: composing voice agents from STT, LLM, TTS, and everything in between, fitting in speech-to-speech models, and getting from prototype to production. Also discussed: why WebRTC remains the right transport for real-world networks, the production realities of observability, cost, and failure modes, how to weigh build-vs-buy, and where voice-native UIs are headed.
WebRTC Live #116: Building Robust Voice AI Pipelines for Every Use Case with Varun Singh
Episode highlights to follow.
Up Next! WebRTC Live #117
Live from RTC.ON
WebRTC.ventures CTO Alberto Gonzalez will be live from the RTC.ON conference in Poland, interviewing several speakers.
Thursday, September 17, 9:30 am Eastern (tentative date and time)
