Conversation intelligence for voice agents: post-call and real-time analytics
Blog post from Deepgram
Conversation intelligence for voice agents has evolved to include real-time analytics that act during live calls, compared to the traditional post-call review process. Real-time analytics help identify and address issues during the call, whereas post-call analytics provide insights for quality assurance, compliance, and agent improvement after a call has ended. The choice of whether to apply analytics during or after a call affects latency, accuracy, and compliance, with transcription accuracy being crucial for downstream intelligence. Deepgram's Audio Intelligence API exemplifies this approach by enabling sentiment analysis, intent recognition, and topic detection from transcribed audio. The document emphasizes the importance of integrating intelligence directly into the voice agent stack to maintain consistency and reduce complexity, while also highlighting the need for regulatory compliance in handling sensitive data like PII and PHI.
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