ElevenLabs demos real-time caller sentiment with Jev

Fast "System One" decision models represent the critical missing layer for voice agents, proving that emotion detection must operate mid-utterance rather than post-call to meaningfully impact conversation outcomes.

• –In-flight emotional telemetry: Offloading classification tasks to specialized low-latency models like Jev (70–500ms) avoids the latency and cost penalties of full generative LLMs while callers are actively speaking.
• –Multi-dimensional sentiment tracking: Monitoring six distinct affective vectors (frustration, happiness, surprise, uncertainty, urgency, neutral) yields actionable nuance compared to traditional, simplistic positive/negative scoring.
• –Proactive de-escalation over retrospective QA: Moving sentiment analysis from post-mortem call recording audits into live runtime enables voice agents and human supervisors to intervene before customer churn occurs.