Deepgram, which offers an enterprise voice AI platform, rolled out Voice Agent API. Voice Agent API lends a unified, voice-to-voice interface that gives developers the control needed to build context-aware voice agents that power natural, responsive conversations.
It combines Deepgram Nova-3 speech-to-text technology, ultra-low-latency Aura-2 text-to-speech, LLM orchestration and contextualized conversational logic to create a unified architecture. This unified API is expected to streamline development without sacrificing control, allowing developers to build while enterprises control orchestration, deployment and model behavior.
“The future of customer engagement is voice-first,” said Deepgram CEO, Scott Stephenson. “But most voice systems today are rigid, fragmented or too slow. With our Voice Agent API, we’re giving developers a powerful yet simple interface to build conversational agents that feel natural, respond instantly and scale across use cases without compromise.”
The platform also offers native, model-driven capabilities such as barge-in handling and turn-taking prediction that reduces the need to stitch together multiple vendors or maintain custom orchestration. This supports streamlined prototyping and reduced complexity.
Built on Deepgram’s enterprise runtime and ownership across the voice AI stack, the platform supports model-level optimization at every layer of the interaction loop. Key capabilities include:
-
Flexible deployment.
-
Runtime-level orchestration.
-
Bring-your-own models.
The system also detects when a user has finished speaking, thus triggering timely response without interruption or lag.
