The Voice AI infrastructure built for conversational AI
Real-time streaming speech recognition optimized for low-latency, natural conversations with LLM-powered agents.
Humanlike text-to-speech synthesis with ultra-low latency for responsive dialogue.
Deepgram Voice Agent API orchestrates STT, TTS, and LLMs with turn-taking, end-of-thought prediction, and barge-in support for seamless conversational flow.
Multi-language support with 30+ STT languages for global deployments.
Private cloud, self-hosted, or hybrid deployment options for full enterprise control.
SDKs, APIs, and docs built for fast developer integration.
Real-time speed built for live voice agents
Conversational AI agents are only as good as their ability to respond instantly. Delays break the flow, frustrate users, and reduce trust. Deepgram’s streaming architecture delivers sub-second round-trip latency across speech-to-text and text-to-speech, keeping your voice agents natural, responsive, and humanlike even at scale.
Built for understanding complex conversations
Deepgram’s AI models are designed for the complexities of real-world conversations, managing speech, timing, and turn taking to deliver fluid, natural interactions.
High-accuracy transcription
Capture words with minimal errors to ensure agents process clean, reliable transcripts.
Custom vocabulary injection
Adapt to business-specific terms, product names, and specialized jargon in real time.
Speaker diarization
Track who’s speaking to maintain context in multi-party conversations.
Topic detection
Identify key topics to help agents follow shifts in intent and conversation flow.
Language detection
Automatically detect spoken language for multilingual conversation support.
End-of-thought detection
Know when users have finished speaking to avoid interruptions or long delays.
