How can AI scale clinical roleplay training beyond what live sessions with human trainers can deliver? For CETA Global, a nonprofit that trains frontline mental health providers around the world, the answer was an AI “flight simulator”: a real-time platform where psychologists practice difficult client sessions with an
Most AI applications operate in turns: a user submits input, the model processes it, and a response is returned. A delay of a second or two goes unnoticed. Live voice AI does not offer that margin. In a roleplay training session where a psychologist practices a difficult
Voice agents are moving out of demos and into production systems that handle customer requests, account actions, healthcare questions, financial details, and support escalations. That changes the security model. A voice agent is listening, deciding, acting, and speaking in real time. That is why voice agent security
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.
