What happens when a model or provider fails during a live voice call?

One thing that’s easy to overlook when building voice agents is what happens when a provider goes down or a model starts returning errors mid conversation.

In a normal API workflow, a failed request might mean retrying or showing an error. In a live voice call, it’s different. The caller is waiting, and a failure in one component shouldn’t bring down the entire conversation.

At Vaani AI @Vaani Developer Platform ,we’ve been working on a multi-layer failover mechanism to handle this:

• Independent fallback chains: Speech recognition, LLM and TTS each have their own backup providers.

• Error-based switching: If the primary provider returns an error, the request moves to the next configured provider.

• Safety-net fallback: Even when an agent is misconfigured, there’s a fallback model available.

• Configurable routing: Teams can choose primary and backup models, use their own API keys, and control whether fallback is enabled.

The important part is that failover happens within the same conversation, rather than forcing the caller to start over.

There’s still a trade off between reliability, latency and consistency when switching providers.

For those building voice AI systems: how do you handle provider failures during an active call? Do you maintain fallback chains for every layer, or rely on retries and timeouts?