Deepgram Flux now available in Telnyx Voice AI

Telnyx now hosts Deepgram’s Flux model inside its global network, enabling sub-second conversational speech recognition. Running Flux at the edge removes public cloud hops, reducing latency for real-time AI voice agents.

What’s new

• Flux integration: Use Deepgram’s Conversational Speech Recognition model within Telnyx Voice AI.
• Edge deployment: Model hosted in Telnyx PoPs alongside telephony and GPU inference layers.
• Low-latency processing: Average end-of-turn detection in ~260 ms.
• Unified pipeline: Handles both transcription and turn detection—no separate VAD setup.
• API access: Available via Mission Control and Telnyx AI Assistants API.

Why it matters

• Reduces speech-to-response latency by 100–300 ms compared to cloud setups.
• Improves barge-in detection for more natural conversations.
• Simplifies configuration by consolidating transcription and endpoint logic.
• Increases reliability by keeping audio within Telnyx’s private backbone.

Example use cases

• Real-time customer support agents with human-like timing.
• Automated appointment scheduling and call routing.
• Interactive voice assistants for logistics or healthcare.

Getting started

1. Log in to Mission Control → AI → Transcription Models.
2. Select Deepgram Flux or set via API:

"transcription": {
  "model": "deepgram/flux",
  "language": "en",
  "settings": {
    "eot_threshold": 0.7,
    "eot_timeout_ms": 5000
  }
}

3. Test live conversations through AI Assistants or the Voice AI API.

Learn more in our developer documentation or contact your Telnyx team.