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Introducing usage-based pricing for Amazon SageMaker AI bidirectional streaming

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Introducing usage-based pricing for Amazon SageMaker AI bidirectional streaming

Usage-based metering for bidirectional streaming solves a software billing problem for real-time speech AI. Customers deploying streaming models on Amazon SageMaker AI bidirectional streaming pay for the endpoint infrastructure that hosts the model. Separately, model providers listing on AWS Marketplace need a way to charge for what customers consume during a live stream. Today, we’re announcing usage-based metering for Amazon SageMaker bidirectional (bidi) streaming inference, so model providers can report actual usage for the AWS Marketplace software charge. Amazon SageMaker AI endpoint infrastructure charges still apply.

Deepgram, the real-time speech AI company, is the launch partner for this capability, bringing usage-based Speech-to-Text (STT) and Text-to-Speech (TTS) billing to AWS Marketplace. This post builds on a series of innovations between Deepgram and AWS. First, we introduced bidirectional streaming for real-time inference on Amazon SageMaker AI, which supports long-lived bidirectional streams between clients and model servers. Then, Deepgram enhanced Amazon SageMaker AI support with AWS Identity and Access Management (AWS IAM) temporary delegation, simplifying secure authentication for enterprise deployments, and expanded observability with enhanced metrics. Now, with usage-based metering, we further strengthen the foundation for production real-time AI, aligning billing with how customers consume streaming and real-time AI workloads.

With AWS Marketplace software metering for SageMaker AI real-time request-response inference, model providers can report a unit count in an HTTP response header. AWS Marketplace uses that quantity for the software charge. This works for request-response APIs where the billable quantity is known when the response is sent.


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