Voice Infrastructure for AI: The Complete Guide | Bandwidth

Voice AI performance depends not only on speech-to-text, language models, text-to-speech, and orchestration, but also on the underlying telephony and network layer that connects calls through the PSTN, manages routing and signaling, and affects latency, reliability, coverage, and compliance. Citing industry research, the discussion argues that production voice agents often exceed the response times associated with natural conversation and that latency spikes can contribute to call abandonment, making network behavior under real-world scale an important consideration. It distinguishes direct PSTN ownership and carrier status from IP backbone or resold connectivity, asserting that direct control can improve troubleshooting and routing accountability. The piece favors keeping telephony infrastructure, AI providers, and orchestration modular rather than purchasing a single bundled stack, enabling organizations to change vendors and isolate failures. It also highlights the need to assess global connectivity, local numbers, regulatory support, SOC 2, HIPAA, GDPR, pricing at scale, and incident response, while describing SIP and WebSocket-based approaches for connecting AI platforms to contact centers through Bandwidth’s Voice API.

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