Article·AI Engineering & Research·Oct 1, 2025

Announcing Deepgram Voice Agent API Integration with AWS Bedrock

For enterprise users in contact centers, healthcare, and customer experience, Deepgram's Voice Agent API integrated with Bedrock unlocks ultra-accurate, real-time speech AI—backed by AWS’s security, scalability, and compliance.

7 min read
Announcing Deepgram Voice Agent API Integration with AWS Bedrock
Headshot of Pippin Bongiovanni

By Pippin Bongiovanni

Senior Product Marketing Manager, Partner Marketing

Last Updated

Deepgram is excited to announce that our Voice Agent API now integrates seamlessly with AWS Bedrock, enabling enterprises to build next-generation conversational AI applications with real-time speech recognition and voice intelligence. This integration brings together Deepgram's specialized speech capabilities with AWS Bedrock's foundation models, empowering enterprise users in contact centers, healthcare, and customer experience (CX) to deploy ultra-accurate, real-time voice agents—backed by AWS's security, scalability, and compliance. Explore this healthcare demo to understand the full potential of this integration.


Technical Details: How Deepgram Voice Agent API Works with AWS Bedrock

Deepgram Voice Agent API + AWS Bedrock Architecture Overview

The Deepgram Voice Agent API integration with AWS Bedrock follows a modular workflow:

  1. Capture: Real-time audio is streamed from applications or call platforms directly into Deepgram’s Speech-to-Text (STT) API.
  2. Analyze: Transcribed text is routed to selected Bedrock foundation models (e.g., Claude, Titan) for reasoning, retrieval-augmented generation (RAG), or classification.
  3. Generate: Bedrock model outputs, including answers or recommended actions, are optionally synthesized back to speech using Deepgram’s Text-to-Speech (TTS).
  4. Respond: Audio responses and structured outputs are delivered instantly, creating truly interactive, human-like conversations

Supported use cases range from voicebots and agent assist to automated summarization, clinical scribing, and appointment scheduling.

API Integration & Orchestration

  • Streaming APIs: Deepgram’s STT and TTS are available as low-latency, scalable APIs—integrate via Lambda for routing or API Gateway endpoints.
  • Function Calling & Reasoning: Bedrock provides direct access to leading LLMs (Claude, Titan, AI21) and supports RAG workflows for contextual queries.
  • Event Hooks: Real-time event hooks allow applications to trigger logic, update databases, or initiate downstream actions based on conversation events (e.g., interruption handling, speaker diarization)

Deepgram Model Capabilities

  • Speech-to-Text: Deepgram models offer sub-second transcription, domain-specific tuning (medical, finance, retail), speaker separation, and background noise resilience. Learn more here.
  • Text-to-Speech: Natural, expressive speech synthesis optimized for dialogue and information delivery. Find additional details on this page.
  • Accuracy & Latency: End-to-end latency (mic-in to voice-out) typically measured in sub-second round trips, ensuring conversational flow even for bursty traffic or high concurrency

Compliance, Security, and Scaling

  • Unified AWS Compliance: Leverage VPC isolation, IAM policies, encryption at rest/in transit, and seamless scaling via AWS best practices. Bedrock’s built-in safety filters and Deepgram’s pipeline design support regulated industries (HIPAA/GDPR).
  • Autoscaling & Failover: Deploy in auto-scaling groups or Kubernetes clusters. Design patterns are available for handling bursty call volumes without degradation or loss of compliance.

AWS Deployment Details

  • AWS Native: Deploy Deepgram STT/TTS within your VPC for minimal latency and maximum compliance.
  • Self-Hosting: Use EC2 AMIs or Docker containers within private subnets; leverage EKS for Kubernetes-based scaling.
  • Network Security: Lock down access using Security Groups/ACLs and AWS PrivateLink, ensuring traffic never leaves your controlled environment.

Quickstart and Resources

  • Sample Code & Reference Architectures: Begin integrating today with GitHub repositories, ready-to-deploy infrastructure guides, and hands-on examples showcased in our recent webinars like this medical assistant voice agent.
  • Getting Started: Provision VPC, deploy Deepgram API, connect to Bedrock endpoints, and customize for your data sources or business logic.Edit your configuration for Bedrock model endpoints, run the provided demos, and scale up as needed.

Why Enterprises Choose Deepgram + AWS Bedrock

  • Seamless, Native Integration: No brittle glue code—deploy straight in your AWS environment.
  • Speed and Accuracy: Optimized for sub-second latency and noise-resistant transcription across complex domains.
  • Compliance First: Security, privacy, and global scaling, with architecture guides for healthcare, finance, and retail verticals.
  • Rapid Innovation: Move from prototype to production fast, leveraging AWS Marketplace for streamlined procurement.

Ready to accelerate your voice AI transformation? Explore the technical resources, join the next webinar for hands-on walkthroughs, and connect with Deepgram or your AWS account team to get started.

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