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	<title>Amazon Bedrock Knowledge Bases &#8211; Noise</title>
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		<title>Amazon FSx for NetApp ONTAP now integrates with Amazon S3 for seamless data access</title>
		<link>https://noise.getoto.net/2025/12/02/amazon-fsx-for-netapp-ontap-now-integrates-with-amazon-s3-for-seamless-data-access/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Tue, 02 Dec 2025 15:59:54 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon FSx for NetApp ONTAP]]></category>
		<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Compute]]></category>
		<category><![CDATA[serverless]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[Access FSx for NetApp ONTAP file data through S3 to enable AI/ML workloads and analytics—letting you use enterprise file data with Bedrock, SageMaker, and analytics services while it remains in your file system.]]></description>
		
		
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		<title>Orchestrating large-scale document processing with AWS Step Functions and Amazon Bedrock batch inference</title>
		<link>https://noise.getoto.net/2025/11/26/orchestrating-large-scale-document-processing-with-aws-step-functions-and-amazon-bedrock-batch-inference/</link>
		
		<dc:creator><![CDATA[Brian Zambrano]]></dc:creator>
		<pubDate>Wed, 26 Nov 2025 21:41:51 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Nova]]></category>
		<category><![CDATA[Amazon Textract]]></category>
		<category><![CDATA[AWS Step Functions]]></category>
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					<description><![CDATA[Organizations often have large volumes of documents containing valuable information that remains locked away and unsearchable. This solution addresses the need for a 
<strong>scalable, automated text extraction and knowledge base pipeline</strong> that transforms static document collections into intelligent, searchable repositories for generative AI applications.]]></description>
		
		
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		<title>Enhance Amazon EMR observability with automated incident mitigation using Amazon Bedrock and Amazon Managed Grafana</title>
		<link>https://noise.getoto.net/2025/08/14/enhance-amazon-emr-observability-with-automated-incident-mitigation-using-amazon-bedrock-and-amazon-managed-grafana/</link>
		
		<dc:creator><![CDATA[Yu-Ting Su]]></dc:creator>
		<pubDate>Thu, 14 Aug 2025 15:25:16 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Agents]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Managed Grafana]]></category>
		<category><![CDATA[Amazon Managed Service for Prometheus]]></category>
		<category><![CDATA[Amazon Nova]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we demonstrate how to integrate real-time monitoring with AI-powered remediation suggestions, combining Amazon Managed Grafana for visualization, Amazon Bedrock for intelligent response recommendations, and AWS Systems Manager for automated remediation actions on Amazon Web Services (AWS).]]></description>
		
		
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		<item>
		<title>Introducing Amazon Bedrock AgentCore: Securely deploy and operate AI agents at any scale (preview)</title>
		<link>https://noise.getoto.net/2025/07/16/introducing-amazon-bedrock-agentcore-securely-deploy-and-operate-ai-agents-at-any-scale-preview/</link>
		
		<dc:creator><![CDATA[Danilo Poccia]]></dc:creator>
		<pubDate>Wed, 16 Jul 2025 15:11:33 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Agents]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Summit New York]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Amazon Bedrock AgentCore enables rapid deployment and scaling of AI agents with enterprise-grade security. It provides memory management, identity controls, and tool integration—streamlining development while working with any open-source framework and foundation model.]]></description>
		
		
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		<title>Introducing Amazon S3 Vectors: First cloud storage with native vector support at scale (preview)</title>
		<link>https://noise.getoto.net/2025/07/16/introducing-amazon-s3-vectors-first-cloud-storage-with-native-vector-support-at-scale-preview/</link>
		
		<dc:creator><![CDATA[Channy Yun (윤석찬)]]></dc:creator>
		<pubDate>Tue, 15 Jul 2025 23:33:32 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon OpenSearch Service]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Summit New York]]></category>
		<category><![CDATA[Featured]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[storage]]></category>
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					<description><![CDATA[Amazon S3 Vectors is a new cloud object store that provides native support for storing and querying vectors at massive scale, offering up to 90% cost reduction compared to conventional approaches while seamlessly integrating with Amazon Bedrock Knowledge Bases, SageMaker, and OpenSearch for AI applications.]]></description>
		
		
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		<item>
		<title>Creando experiencias de cliente con IA mediante un hub de comunicaciones moderno</title>
		<link>https://noise.getoto.net/2025/07/12/creando-experiencias-de-cliente-con-ia-mediante-un-hub-de-comunicaciones-moderno/</link>
		
		<dc:creator><![CDATA[Bruno Giorgini]]></dc:creator>
		<pubDate>Fri, 11 Jul 2025 22:35:37 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Agents]]></category>
		<category><![CDATA[Amazon Bedrock Guardrails]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Q]]></category>
		<category><![CDATA[AWS]]></category>
		<category><![CDATA[AWS End User Messaging]]></category>
		<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=80483997730c417b69e50e039d507b5c</guid>

					<description><![CDATA[Los clientes de hoy esperan que las organizaciones satisfagan proactivamente sus necesidades con contenido personalizado, entregado en el momento, lugar y forma de su elección. Buscan interacciones dinámicas y conscientes del contexto con conversaciones sofisticadas a través de todos los canales de comunicación. Esta creciente demanda ejerce presión sobre las organizaciones para transformar sus flujos […]]]></description>
		
		
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		<item>
		<title>Amazon Bedrock baseline architecture in an AWS landing zone</title>
		<link>https://noise.getoto.net/2025/06/23/amazon-bedrock-baseline-architecture-in-an-aws-landing-zone/</link>
		
		<dc:creator><![CDATA[Abdel-Rahman Awad]]></dc:creator>
		<pubDate>Mon, 23 Jun 2025 18:36:51 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Guardrails]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Route 53]]></category>
		<category><![CDATA[Amazon VPC]]></category>
		<category><![CDATA[Architecture]]></category>
		<category><![CDATA[architecture best practices]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[security]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<category><![CDATA[VPC]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ebcee71fc53279a51e38784b1450a242</guid>

					<description><![CDATA[In this post, we explore the Amazon Bedrock baseline architecture and how you can secure and control network access to your various Amazon Bedrock capabilities within AWS network services and tools. We discuss key design considerations, such as using Amazon VPC Lattice auth policies, Amazon Virtual Private Cloud (Amazon VPC) endpoints, and AWS Identity and Access Management (IAM) to restrict and monitor access to your Amazon Bedrock capabilities.]]></description>
		
		
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			</item>
		<item>
		<title>Empower financial analytics by creating structured knowledge bases using Amazon Bedrock and Amazon Redshift</title>
		<link>https://noise.getoto.net/2025/05/20/empower-financial-analytics-by-creating-structured-knowledge-bases-using-amazon-bedrock-and-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Nita Shah]]></dc:creator>
		<pubDate>Tue, 20 May 2025 16:44:44 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[generative AI]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=102b00e088a076972e687fbdfa81f7f8</guid>

					<description><![CDATA[In this post, we showcase how financial planners, advisors, or bankers can now ask questions in natural language. These prompts will receive precise data from the customer databases for accounts, investments, loans, and transactions. Amazon Bedrock Knowledge Bases automatically translates these natural language queries into optimized SQL statements, thereby accelerating time to insight, enabling faster discoveries and efficient decision-making.]]></description>
		
		
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		<item>
		<title>AWS Weekly Roundup: Omdia recognition, Amazon Bedrock RAG evaluation, International Women’s Day events, and more (March 24, 2025)</title>
		<link>https://noise.getoto.net/2025/03/24/aws-weekly-roundup-omdia-recognition-amazon-bedrock-rag-evaluation-international-womens-day-events-and-more-march-24-2025/</link>
		
		<dc:creator><![CDATA[Betty Zheng (郑予彬)]]></dc:creator>
		<pubDate>Mon, 24 Mar 2025 17:15:01 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock Guardrails]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Nova]]></category>
		<category><![CDATA[Amazon Q]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS WAF]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[Week in Review]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=06f5b9e97187ce05f592891917568f49</guid>

					<description><![CDATA[As we celebrate International Women’s Day (IWD) this March, I had the privilege of attending the ‘Women in Tech’ User Group meetup in Shenzhen last weekend. I was inspired to see over 100 women in tech from different industries come together to discuss AI ethics from a female perspective. Together, we explored strategies such as […]]]></description>
		
		
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		<item>
		<title>New RAG evaluation and LLM-as-a-judge capabilities in Amazon Bedrock</title>
		<link>https://noise.getoto.net/2024/12/02/new-rag-evaluation-and-llm-as-a-judge-capabilities-in-amazon-bedrock/</link>
		
		<dc:creator><![CDATA[Danilo Poccia]]></dc:creator>
		<pubDate>Mon, 02 Dec 2024 03:21:31 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=7ed261ebc9acadb17ee47a380f6ce697</guid>

					<description><![CDATA[Evaluate AI models and applications efficiently with Amazon Bedrock’s new LLM-as-a-judge capability for model evaluation and RAG evaluation for Knowledge Bases, offering a variety of quality and responsible AI metrics at scale.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>New APIs in Amazon Bedrock to enhance RAG applications, now available</title>
		<link>https://noise.getoto.net/2024/12/01/new-apis-in-amazon-bedrock-to-enhance-rag-applications-now-available/</link>
		
		<dc:creator><![CDATA[Veliswa Boya]]></dc:creator>
		<pubDate>Sun, 01 Dec 2024 20:51:24 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Knowledge Bases]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=8c5e99c1d5118f06d213d4eb5b1ede8f</guid>

					<description><![CDATA[With custom connectors and reranking models, you can enhance RAG applications by enabling direct ingestion to knowledge bases without requiring a full sync, and improving response relevance through advanced re-ranking models.]]></description>
		
		
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