Introducing the VideoSDK Fallback Adapter: Keep Voice Agents Talking When Providers Fail

VideoSDK’s Fallback Adapter is designed to improve the reliability of production AI voice agents by automatically switching among speech-to-text, language-model, and text-to-speech providers when a provider fails or becomes persistently slow during a live session. Developers configure an ordered set of primary and backup providers for each pipeline stage, while the adapter monitors errors and relevant latency metrics, including STT latency, LLM time to first token, and TTS time to first byte. Error-based fallback is enabled through provider lists and recovery settings, while latency-based fallback is optional and triggers only after a configurable number of consecutive slow interactions. Failed providers enter a cooldown period before being retried, healthy higher-priority providers can be restored automatically, and repeatedly unsuccessful providers can be permanently disabled after a set number of recovery attempts. The approach aims to replace custom retry, health-check, and recovery logic with configuration options that help preserve conversational continuity despite provider outages, throttling, or performance degradation.

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