Voice AI That Actually Works in Production
Voice AI That Actually Works in Production
Voice AI has moved quickly from novelty to practical deployment — but most of the teams building voice agents come from an AI background, not a communications one. That gap shows up in production: latency that breaks the conversational flow, poor handling of real-world audio conditions, architectures that can't scale, and integrations with telephony infrastructure that were clearly bolted on as an afterthought.
We come at this from the other direction. We know voice infrastructure deeply — across SIP, WebRTC, and the open source media ecosystem — and we build AI into it, rather than building AI systems and trying to attach a phone number to them. Jambonz is a strong foundation for voice AI applications and one we know particularly well. Our voice AI work includes real-time conversational agents built on pipelines like pipecat, deployment via WhatsApp Business Calling, WhatsApp AI agents for messaging-based automation, and integration with existing SIP and WebRTC infrastructure so your voice AI works within your existing telephony estate rather than alongside it.
We build voice agents that handle the things that make voice hard: turn-taking, interruption, poor audio quality, silence detection, and the expectation that a voice interaction should feel like talking to someone who knows what they're doing.
- Real-time voice agent development (pipecat and similar)
- WhatsApp Business Calling integration for voice AI
- WhatsApp AI agents for conversational automation
- SIP and WebRTC integration for existing telephony estates
- Contact centre voice AI and IVR modernisation
