Build speech recognition and spoken responses into products

What is Deepgram Voice AI?

Deepgram is voice AI infrastructure for application builders. Its APIs cover converting speech into text, producing spoken output, and coordinating conversations with language models and business systems. This makes it relevant to products where audio is an input, an output, or both. The central engineering task is choosing how speech connects with the application's logic, including the points where the system should act, ask for clarification, or stop.

Choose a component or a connected voice workflow

Deepgram offers separate speech-to-text, text-to-speech, and audio-intelligence capabilities alongside a unified Voice Agent API. The agent workflow combines speech recognition, language-model orchestration, and speech generation, with function calling for external actions or information. Its documentation of the architecture distinguishes audio transport, model behavior, business logic, and external systems, helping teams identify which responsibilities remain in their own application.

Evaluate realistic audio and failure cases

Test recordings and live interactions that resemble your actual users, including accents, background noise, pauses, and interruptions. Measure whether the application completes its task, not merely whether a transcript looks plausible. Define how names, numbers, and uncertain requests are confirmed. For spoken responses, review pacing and clarity in context, and keep an explicit recovery path when recognition or an external service fails.

Features to explore

• Speech-to-text API
• Text-to-speech API
• Voice Agent API
• Audio intelligence
• Function calling

Who is Deepgram Voice AI for?

Developers building transcription, audio analysis, or conversational products. It is a suitable fit when speech needs to connect with custom application logic and the team can evaluate performance using representative recordings and real workflows.

Before you get started

Test language, audio-format, and deployment support for your use case. Review retention, regional processing, and integration permissions, and verify critical spoken details before allowing an agent to perform consequential actions.