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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. This systematic approach leads to more reliable and standardized evaluations.

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Implementing a Version Control System for AWS QuickSight

Xebia

Among the myriads of BI tools available, AWS QuickSight stands out as a scalable and cost-effective solution that allows users to create visualizations, perform ad-hoc analysis, and generate business insights from their data. AWS does not provide a comprehensive list of supported dataset types.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

The process involves the collection and analysis of extensive documentation, including self-evaluation reports (SERs), supporting evidence, and various media formats from the institutions being reviewed. As part of the CIC program, BQA has built a proof of concept solution, harnessing the power of AWS services and generative AI capabilities.

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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. This post is the first in a series covering AWS MCP Servers.

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Data Analytics in the Cloud for Developers and Founders

Speaker: Javier Ramírez, Senior AWS Developer Advocate, AWS

Can business people create reports via drag and drop? In this session, we address common pitfalls of building data lakes and show how AWS can help you manage data and analytics more efficiently. Can data scientists discover and use the data? Can operations monitor what’s going on? Is your data secure?

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning - AI

Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. Field Advisor serves four primary use cases: AWS-specific knowledge search With Amazon Q Business, weve made internal data sources as well as public AWS content available in Field Advisors index.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. On AWS, you can use the fully managed Amazon Bedrock Agents or tools of your choice such as LangChain agents or LlamaIndex agents.