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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning - AI

As these AI technologies become more sophisticated and widely adopted, maintaining consistent quality and performance becomes increasingly complex. Key features Before diving into the implementation details, we examine the key features that make the capabilities of RAG evaluation on Amazon Bedrock Knowledge Bases particularly powerful.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

In this post, we propose an end-to-end solution using Amazon Q Business to simplify integration of enterprise knowledge bases at scale. This solution ingests and processes data from hundreds of thousands of support tickets, escalation notices, public AWS documentation, re:Post articles, and AWS blog posts.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

In this post, we demonstrate how to create an automated email response solution using Amazon Bedrock and its features, including Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , and Amazon Bedrock Guardrails. Monitoring – Monitors system performance and user activity to maintain operational reliability and efficiency.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This systematic approach leads to more reliable and standardized evaluations.

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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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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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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions. Haiku model to receive answers to an array of questions because it’s a performant, fast, and cost-effective option.