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Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do in your RAG workflows.

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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. Solution overview This section outlines the architecture designed for an email support system using generative AI.

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Create a generative AI-based application builder assistant using Amazon Bedrock Agents

AWS Machine Learning - AI

They use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide a final response to the end user. We use Amazon Bedrock Agents with two knowledge bases for this assistant.

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AWS empowers sales teams using generative AI solution built on Amazon Bedrock

AWS Machine Learning - AI

Our internal AI sales assistant, powered by Amazon Q Business , will be available across every modality and seamlessly integrate with systems such as internal knowledge bases, customer relationship management (CRM), and more. Clear restrictions – Specify important limitations upfront. Don’t make up any statistics.”