Remove Knowledge Base Remove Scalability Remove Software Review
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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. This time efficiency translates to significant cost savings and optimized resource allocation in the review process.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. Developers need code assistants that understand the nuances of AWS services and best practices.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. Its sales analysts face a daily challenge: they need to make data-driven decisions but are overwhelmed by the volume of available information.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Through advanced data analytics, software, scientific research, and deep industry knowledge, Verisk helps build global resilience across individuals, communities, and businesses. Verisk has a governance council that reviews generative AI solutions to make sure that they meet Verisks standards of security, compliance, and data use.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

Amazon Bedrock Agents coordinates interactions between foundation models (FMs), knowledge bases, and user conversations. The agents also automatically call APIs to perform actions and access knowledge bases to provide additional information. The documents are chunked into smaller segments for more effective processing.

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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning - AI

They offer fast inference, support agentic workflows with Amazon Bedrock Knowledge Bases and RAG, and allow fine-tuning for text and multi-modal data. To do so, we create a knowledge base. Complete the following steps: On the Amazon Bedrock console, choose Knowledge Bases in the navigation pane.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.