Ai-calling-architecture

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Why Your AI Voice Agent Demo Worked Perfectly But Production Failed: The Demo-to-Production Gap That Kills 60% of AI Calling Deployments

AI Calling ProductionVoice AI DeploymentAI Agent FailureDemo vs ProductionAI Calling LatencyModel DriftAI Voice QualityTough Tongue AIAI Calling ArchitectureProduction AI Scaling

Why 60% of AI voice agent deployments fail between demo and production. Covers the 7 technical failure modes: latency degradation under load, STT accuracy collapse in real-world noise, model drift over time, hallucination escalation, telephony infrastructure fragility, conversation state management failures, and the observability gap. Includes the exact diagnostic framework and production hardening checklist used by teams that survive the transition.

AI Calling Architecture Explained: How SIP, LLM, TTS, and STT Work Together to Make AI Phone Calls (2026)

AI CallingAI Calling ArchitectureSIPLLMText to SpeechSpeech to TextVoice AITough Tongue AIAI InfrastructureConversational AI

A deep technical explainer on how AI calling actually works under the hood. Learn how SIP, STT, LLM, and TTS components work together in real time to create natural AI phone conversations, the latency budget for each component, and why Tough Tongue AI abstracts all this complexity into a no-code platform.