When Jeff Pulver invited me to attend Voice and Conversations on the Net (VON) 2026 on behalf of WebRTC.ventures, I accepted immediately. Three days with people building the next generation of voice communications was an easy yes. While at the conference earlier this week, the enthusiasm for
As Voice AI becomes more prevalent, applications need a way to store conversation data that supports observability, auditing, and long-term retention. The audio recording or a text transcript alone leaves out critical context. Additional details matter too, such as who was in the conversation, what devices were
Voice AI systems generate more than recordings and transcripts. Every production interaction produces a web of artifacts across multiple systems: call-setup metadata, ASR output, LLM responses, tool calls, CRM updates, escalation events, and compliance-relevant signals like caller identity verification. Most Voice AI architectures store some of these.
