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The demand for real-time, low-latency voice AI within secure enterprise cloud environments is rapidly growing. Deepgram has announced a native integration with Amazon SageMaker AI, deploying its streaming speech-to-text, text-to-speech, and Voice Agent APIs as real-time SageMaker endpoints. This allows developers to build and scale voice-powered applications directly within their existing AWS workflows, maintaining stringent security and compliance while achieving sub-second latency.
Deepgram integrates streaming Voice AI models as native Amazon SageMaker AI endpoints.
The offering includes real-time speech-to-text, text-to-speech, and Voice Agent APIs.
It delivers sub-second latency for high-scale use cases like contact centers and trading.
Data remains within the AWS environment, supporting VPC deployment for compliance.
The integration simplifies deployment, removing the need for custom pipelines.
Deepgram is an AWS Generative AI Competency Partner with a Strategic Collaboration Agreement.
This native integration is designed to remove infrastructure complexity for AWS customers. By offering Deepgram's capabilities as SageMaker real-time endpoints, developers can access streaming speech models directly through the familiar SageMaker API, specifically using for bidirectional streaming. This eliminates the need for custom orchestration or workarounds, allowing teams to focus on building voice-driven applications—such as interactive voice agents or live conversation analytics—within their established AWS security and operational frameworks.
The solution is built for enterprise demands, prioritizing low latency, high reliability, and data governance. It delivers sub-second latency, which is critical for real-time interactions in sectors like financial trading and contact centers. Organizations can deploy Deepgram within their Amazon Virtual Private Cloud (VPC) or as a managed service, ensuring that voice data remains within their controlled AWS environment. This architecture directly addresses data residency, privacy, and compliance requirements, making advanced voice AI accessible for regulated industries.
The integration is underpinned by a strengthened alliance between Deepgram and AWS, including a multi-year Strategic Collaboration Agreement and Deepgram's status as an AWS Generative AI Competency Partner. This partnership aims to accelerate enterprise adoption by embedding state-of-the-art voice capabilities into the core AWS service ecosystem. For AWS customers, it expands the utility of SageMaker, providing a powerful, streamlined path to incorporate realistic and responsive voice AI into their products and internal workflows.
Deepgram's move to embed its technology within Amazon SageMaker represents a significant lowering of the barrier to entry for sophisticated voice AI. By aligning with the predominant cloud platform for machine learning, Deepgram ensures its high-accuracy, low-latency models are accessible where enterprises are already building. This integration not only simplifies technical deployment but also strategically positions voice AI as a fundamental, integrated component of the modern AI application stack within the cloud.
About Deepgram
Deepgram is the world’s most realistic and real-time Voice AI platform, offering speech-to-text (STT), text-to-speech (TTS), and full speech-to-speech (STS) capabilities–all powered by its enterprise-grade runtime. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through cloud APIs or as self-hosted / on-premises APIs – due to its unmatched accuracy, low latency, and pricing. Customers include technology ISVs building voice products or platforms, co-sell partners working with large enterprises, and enterprises solving internal use cases. Having processed over 50,000 years of audio and transcribed over 1 trillion words, there is no organization in the world that understands voice better than Deepgram.
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