Deepgram

Cloud-based Whisper model integration for transcription.

HTTP-based API for speech-to-text, text-to-speech, and audio intelligence.

WebSocket protocol for real-time streaming and low-latency applications.

Extract actionable insights from conversational audio and text at scale.

Recognize user intent from conversational audio.

Analyze sentiment in conversational audio and text.

Automatically summarize audio and text content.

Automatically detect topics in conversational audio.

Integrated language model orchestration within the Voice Agent API.

Convert audio to text with high accuracy. Supports 45+ languages with Nova models.

Generate natural, low-latency speech for voice assistants and conversational AI applications using Aura models.

Real-time conversational AI agents that handle interruptions, take complex actions, and deliver natural responses with built-in turn detection.

Pre-recorded audio processing for bulk transcription jobs.

Deploy Deepgram APIs on Deepgram's managed cloud infrastructure.

Deploy Deepgram on your own infrastructure for complete control.

Real-time streaming audio processing with low latency.

Build and deploy custom voice AI models for enterprise-specific workflows.

Opt-in program to help improve Deepgram models with your usage data.

Automatically detect the language of incoming audio.

Boost accuracy for specific domain-specific jargon, product names, or acronyms important to your use case.

Automatically identify and remove sensitive PII such as social security numbers, credit cards, and phone numbers.

Automatically format punctuation, casing, dates, and currency for readability.

Detect multiple speakers and label who spoke when in the transcript.

Text-to-speech model for voice assistants and conversational AI applications.

Natural, low-latency text-to-speech model for voice applications.