Deepgram

Combines speech-to-text, text-to-speech, and large language model orchestration into a single API to reduce complexity, latency, and cost for building conversational AI agents.

A speech-to-text model optimized for real-time conversation with built-in turn detection, natural interruption handling, and sub-300ms latency for human-like voice agents.

High-performance speech-to-text model offering top accuracy, multilingual support, and noise robustness for production transcription needs.

Specialized models optimized for domains like healthcare, legal, and finance, plus custom models trained on proprietary datasets for maximum accuracy.

Includes summarization, topic detection, sentiment analysis, and intent recognition powered by task-specific language models that work with or without transcription.

Ability to transcribe multichannel audio with speaker diarization and separate channel billing for accurate transcription in overlapping speech scenarios.

Responsive, natural-sounding text-to-speech models designed for high-throughput voicebots and conversational AI applications, billed per character.

Offers cloud and self-hosted deployment options, priority support, and compliance-ready solutions for large volume and sensitive data environments.