Deepgram

Deepgram is a voice AI platform that helps you transcribe audio, generate natural speech, and build conversational voice applications with low latency, scalable infrastructure, and APIs designed for real-time production environments.

Deepgram is a voice AI platform designed for teams building products around speech, audio, and conversational interfaces. The platform combines speech-to-text, text-to-speech, and voice agent orchestration into a single API suite that can support everything from live transcription tools to AI-powered call automation.

The speech recognition engine is particularly strong in real-time environments where latency matters. It processes live audio streams quickly and handles accents, background noise, and overlapping conversations better than many older speech systems. That makes it a practical option for customer support platforms, meeting assistants, voice analytics products, and live captioning applications.

On the synthesis side, Deepgram generates natural-sounding voices that feel far less robotic than traditional text-to-speech systems. You can use it for conversational agents, automated phone systems, or any workflow that requires spoken responses in real time.

The Voice Agent API adds another layer by connecting transcription, language models, and speech generation into a unified pipeline. You can build conversational AI experiences without maintaining separate vendors and infrastructure for each voice component.

Key features

• Real-time speech-to-text transcription — Deepgram converts live audio into text with very low latency, making it useful for captioning, customer support systems, voice assistants, and applications where delayed responses would noticeably hurt the experience.
• Voice Agent API — The Voice Agent API combines speech recognition, language model orchestration, and speech generation into one workflow, reducing integration complexity and improving responsiveness for conversational AI applications operating in real time.
• Custom model training — Enterprise customers can fine-tune models using industry-specific terminology and proprietary audio data, improving recognition accuracy for specialized sectors like healthcare, legal services, insurance, financial operations, and technical support environments.