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Integrating AWS API MCP Server with Amazon Quick using Amazon Bedrock AgentCore Runtime

Integrating AWS API MCP Server with Amazon Quick using Amazon Bedrock AgentCore Runtime

As your AWS infrastructure scales, operational workflows naturally grow more complex. SREs and DevOps Engineers spend significant time context-switching between the AWS Management Console, CLI documentation, and multiple service dashboards. They manually translate business questions into the correct API syntax, chain calls across services, and rebuild the same integration patterns for each new use case.This …

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Building multi-tenant agents with Amazon Bedrock AgentCore

Building multi-tenant agents with Amazon Bedrock AgentCore

Software as a service (SaaS) providers building multi-tenant agentic applications must address architectural challenges beyond the typical concerns of security, governance, and response accuracy. These include tenant isolation, tenant identity, tenant observability, data isolation, cost attribution, and noisy neighbor mitigation. Closing the gap between a working demo and a production deployment requires infrastructure built for …

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Break the context window barrier with Amazon Bedrock AgentCore

Break the context window barrier with Amazon Bedrock AgentCore

When you analyze documents that span millions of characters, you hit the context window barrier and even the largest context windows fall short. Your model either rejects the input or produces answers based on incomplete information. How do you reason over documents that don’t fit? In this post, you will learn how to implement Recursive …

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Build AI agents for business intelligence with Amazon Bedrock AgentCore

Build AI agents for business intelligence with Amazon Bedrock AgentCore

OPLOG, a technology-driven fulfillment company powered by AI and robotics, processes millions of items monthly across Türkiye, the United Kingdom, and Germany for major brands and global marketplaces. Operating a customer-agnostic fulfillment model where multiple brands share warehouse infrastructure, workers, and autonomous robots, OPLOG faced a challenge common to many B2B organizations: fragmented business data …

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Build an AI-powered recruitment assistant using Amazon Bedrock

Build an AI-powered recruitment assistant using Amazon Bedrock

According to a people management survey of 748 HR leaders, recruiters spend an average of 17.7 hours per vacancy on administrative work. That’s more than two working days per hire. A separate 2024 SmartRecruiters survey found that 45% of talent acquisition leaders spend more than half their working hours on tasks that could be automated. …

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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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