Deepgram, known for delivering the world’s most realistic and real-time Voice AI platform, has announced a major milestone by launching a native integration with Amazon SageMaker AI. With this move, the company enables seamless access to streaming, real-time speech-to-text (STT), text-to-speech (TTS), and its Voice Agent API directly through Amazon SageMaker AI real-time endpoints without requiring custom pipelines or complex orchestration. As a result, teams can now build, deploy, and scale voice-driven applications within their existing AWS workflows while preserving the security and compliance benefits of their AWS environment.
“Deepgram’s integration with Amazon SageMaker represents an important step forward for real-time voice AI” said Scott Stephenson, CEO and Co-Founder, Deepgram.
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Expanding on this announcement, Stephenson emphasized the transformative impact of this collaboration. “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,” he said.
Moreover, the integration introduces native streaming through Amazon SageMaker endpoints, eliminating the need for technical workarounds. This ensures real-time inference with sub-second latency, making it ideal for high-volume, time-sensitive use cases like trading floors, contact centers, and live analytics environments.
Deepgram designed the solution to run directly on AWS, supporting streaming responses through InvokeEndpointWithResponseStream while ensuring that all data remains within AWS infrastructure. Customers can implement Deepgram in their Amazon Virtual Private Cloud (Amazon VPC) or use it as a managed service, helping them meet stringent compliance and data residency demands.
Stephenson further underscored the importance of scalability and simplicity for enterprise teams. “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.”
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Additionally, this integration strengthens Deepgram’s long-standing relationship with AWS. The company is an AWS Generative AI Competency Partner and recently entered a multi-year Strategic Collaboration Agreement (SCA) with AWS to accelerate the enterprise use of voice AI.
Highlighting the value for AWS users, Ankur Mehrotra, general manager for Amazon SageMaker at AWS, said, “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.”
With this integration, Deepgram and AWS are jointly empowering enterprises to adopt scalable, secure, and high-performance voice AI capabilities paving the way for more advanced, real-time conversational experiences across industries.
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