Choosing a low-latency infrastructure layer for conversational AI

Low latency is presented as essential to effective conversational AI in call centers because delays can create perceived dead air, frustrate callers, and lead to abandoned calls. The article argues that latency often results less from LLM inference than from fragmented infrastructure that moves audio among telephony, media servers, speech recognition, language models, and text-to-speech systems. It advocates for a unified voice pipeline that combines real-time transcription and speech synthesis while remaining compatible with different LLMs, knowledge bases, and voice providers. Twilio positions its ConversationRelay WebSocket API as such an infrastructure layer, citing internal benchmarks of median latency below 0.5 seconds and 95th-percentile latency below 0.725 seconds, along with features including interruption support, context preservation, and integration with existing AI stacks.

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