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Build AI-powered dashboard automation agents with NLP on Amazon Bedrock AgentCore

Build AI-powered dashboard automation agents with NLP on Amazon Bedrock AgentCore

Business analysts often wait days for dashboard modifications when responding to changing business requirements. Traditional processes involve submitting modification requests to IT teams, who interpret requirements, navigate API documentation, understand table schemas, and deploy changes. While this approach maintains proper oversight and quality control, it can result in multi-day turnaround times when rapid dashboard updates …

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Announcing OpenAI-compatible API support for Amazon SageMaker AI endpoints

Announcing OpenAI-compatible API support for Amazon SageMaker AI endpoints

Today, Amazon SageMaker AI introduces OpenAI-compatible API support for real-time inference endpoints. If you use the OpenAI SDK, LangChain, or Strands Agents, you can now invoke models on SageMaker AI by changing only your endpoint URL. You don’t need a custom client, a SigV4 wrapper, or code rewrites. Overview With this launch, SageMaker AI endpoints …

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Multimodal evaluators: MLLM-as-a-judge for image-to-text tasks in Strands Evals

Multimodal evaluators: MLLM-as-a-judge for image-to-text tasks in Strands Evals

If you’re building visual shopping, image or document understanding, or chart analysis, you need a way to verify whether your model’s response is actually grounded in the source image. A text-only evaluator cannot tell you whether a caption faithfully describes an image, whether an extracted invoice total matches the document, or whether a screen summary …

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Build real-time voice applications with Amazon SageMaker AI and vLLM

Build real-time voice applications with Amazon SageMaker AI and vLLM

Voice agents, live captioning, contact center analytics, and accessibility tools all depend on real-time speech-to-text, where your application streams audio in and receives transcription back simultaneously over a single persistent connection. Traditional request-response inference falls short here because transcription cannot begin until the entire audio recording has been received, adding latency that breaks the real-time …

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