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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

In this new era of emerging AI technologies, we have the opportunity to build AI-powered assistants tailored to specific business requirements. Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Chatbots are used to build response systems that give employees quick access to extensive internal knowledge bases, breaking down information silos. While useful, these tools offer diminishing value due to a lack of innovation or differentiation. This makes their wide range of capabilities usable. An LLM can do that too.

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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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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. These indexed documents provide a comprehensive knowledge base that the AI agents consult to inform their responses.

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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning - AI

Seamless integration of latest foundation models (FMs), Prompts, Agents, Knowledge Bases, Guardrails, and other AWS services. Flexibility to define the workflow based on your business logic. Knowledge base node : Apply guardrails to responses generated from your knowledge base.

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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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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. Choose Next.