Deepgram Announces Native Integration with Amazon SageMaker AI to Advance Real-Time Voice AI Deployment for Enterprises
Deepgram, recognized globally as one of the most advanced platforms for real-time and highly accurate Voice AI, has announced a significant milestone in enterprise AI enablement: a native integration with Amazon SageMaker AI. This collaboration now allows organizations to access Deepgram’s streaming speech-to-text (STT), text-to-speech (TTS), and Voice Agent API capabilities directly as SageMaker AI real-time endpoints, without the need for custom engineering pipelines or complex orchestration layers. With this integrated offering, development teams can seamlessly build, deploy, and scale voice-powered applications entirely within their current AWS environment, while preserving full compliance, privacy, and operational security.
According to Scott Stephenson, CEO and Co-Founder of Deepgram, this collaboration represents an important breakthrough for the future of voice-driven artificial intelligence.
Deepgram’s integration with Amazon SageMaker represents an important step forward for real-time voice AI. By bringing our streaming speech models directly into SageMaker, enterprises can deploy speech-to-text, text-to-speech, and voice agent capabilities with sub-second latency, all within their AWS environment. This collaboration extends SageMaker’s functionality and gives developers a powerful way to build and scale voice-driven applications securely and efficiently,” Stephenson stated.
Eliminating Deployment Complexity and Reducing Latency for High-Scale Voice Applications
One of the core advancements brought by this integration is the ability for teams to run native streaming inference through Amazon SageMaker endpoints. This ensures real-time performance without workarounds or time-consuming custom development. Instead of requiring external routing or third-party systems, enterprises can now run Deepgram’s advanced voice models directly from the SageMaker API with minimal setup.
The integration delivers sub-second latency, a crucial factor for mission-critical and real-time voice use cases such as:
- Customer contact centers requiring rapid AI-driven responses and insights
- Financial trading floors, where immediate voice execution and compliance monitoring are essential
- Live analytics for media, broadcast, healthcare, and emergency services
- Voice assistants, conversational AI, and automated customer experience systems
- Call intelligence and transcription for regulated industries like banking and insurance
By providing enterprise-grade reliability and scalable performance, Deepgram enables organizations to harness voice AI for improved decision-making, customer engagement, and operational automation without risking delays or reliability issues.
Designed for Enterprise Security and Built to Run Natively in AWS Environments
The integration is engineered specifically for organizations operating within strict governance, data residency, and compliance frameworks. Built to run entirely on AWS, the combined solution supports streaming responses through InvokeEndpointWithResponseStream, ensuring that data remains contained within AWS infrastructure. Companies can deploy Deepgram within their own Amazon Virtual Private Cloud (Amazon VPC) or use it as a fully managed service, depending on operational needs.
This approach gives enterprises greater control over sensitive voice data, making the solution suitable for industries governed by stringent regulations such as HIPAA, PCI, SOC, GDPR, and financial compliance requirements.
Stephenson emphasized this point further by stating:
Enterprise developers need to build voice AI applications at scale without compromising on speed, accuracy, or security. Our native integration with Amazon SageMaker removes the complexity from deploying real-time voice capabilities, allowing AWS customers to focus on innovation rather than infrastructure. By bringing our state-of-the-art speech models directly into the AWS environment where companies already operate, we’re making it dramatically easier for organizations to create voice experiences that truly transform how they engage with customers and analyze conversations at scale.
Strengthening Deepgram and AWS Partnership to Expand Generative Voice AI Adoption
This integration builds on a growing strategic relationship between Deepgram and AWS. Deepgram is already recognized as an AWS Generative AI Competency Partner, a designation awarded to companies demonstrating deep expertise in delivering enterprise-ready AI solutions. Additionally, Deepgram has signed a multi-year Strategic Collaboration Agreement (SCA) with AWS to accelerate global adoption of scalable voice AI technology.
Ankur Mehrotra, General Manager for Amazon SageMaker at AWS, highlighted the significance of this advancement for the AWS ecosystem:
Deepgram’s new Amazon SageMaker AI integration makes it simple for customers to bring real-time voice capabilities into their AWS workflows. By offering streaming speech-to-text and text-to-speech directly through Amazon SageMaker endpoints, Deepgram helps developers accelerate innovation while maintaining data security and compliance on AWS. This integration is a great example of how Deepgram is expanding its market reach by making generative AI more accessible and powerful through AWS services, while enabling our mutual customers to build sophisticated voice applications.
Enabling the Next Generation of Voice-Enabled Intelligent Applications
Voice technology has emerged as one of the fastest-growing categories in enterprise AI, driven by increasing demand for automation, customer experience transformation, and real-time analytics. As organizations pursue large-scale modernization and AI transformation, voice is becoming a central component of digital service strategies.
The Deepgram-SageMaker integration provides developers with powerful new opportunities, including:
- Automated call handling with real-time transcription and conversational responses
- Voice-driven generative AI workflows for automated support, chatbots, and knowledge retrieval
- Real-time multilingual transcription and translation
- High-accuracy dictation and voice-to-application interfaces
- Advanced call scoring and analytics, including sentiment analysis and compliance monitoring
Because the technology runs natively within AWS, organizations can scale deployment from pilot to full enterprise rollout without disruption, major migrations, or new security frameworks.
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