I recently presented “Building Real-Time Voice AI: From Pipelines to Conversations” at the Nashua Cloud .NET User Group, where we explored how Voice AI is evolving beyond rigid pipelines like Speech → Text → LLM → Text → Speech. Traditional approaches introduce latency, break conversational flow, and make interactions feel unnatural. With the rise of real-time, audio-native LLMs, voice systems can now reason directly over audio, enabling low-latency, streaming, and interruptible conversations that feel far more human. In this session, I explain how GPT-Realtime works, when real-time voice AI makes sense, and how enterprises can combine conversational AI with workflows, tools, and governance to build reliable, production-ready systems.
The talk also includes a 10-minute demo of Vapi.ai, showcasing their real-time video chat and voice APIs for building interactive voice experiences with minimal orchestration overhead. It demonstrates how modern voice agents can handle natural interruptions, reduce response latency, and deliver more engaging user experiences compared to traditional voice pipelines. I also walk through hybrid architectures that combine real-time LLMs for conversation with deterministic workflows for business logic, tool execution, and compliance requirements—an approach that works well for enterprise-grade voice assistants, copilots, and support systems.
Thank you to everyone who joined, asked thoughtful questions, and contributed to a great discussion.
The Recording and sample codes are available here:
Watch the session: https://youtu.be/k5DtBUoXSvY
Presentation: https://www.slideshare.net/slideshow/building-real-time-voice-ai-udaiappa-ramachandran/285076305
Sample Code: https://github.com/nhcloud/voicechat
If you missed the session, join us at the next Nashua Cloud .NET User Group (NashuaUG) meetup to continue exploring practical, real-world AI engineering.