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

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

APIs 128
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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.

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Dynamic metadata filtering for Amazon Bedrock Knowledge Bases with LangChain

AWS Machine Learning

Amazon Bedrock Knowledge Bases offers a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) to internal data sources. In this post, we discuss using metadata filters with Amazon Bedrock Knowledge Bases. For instructions, see Create an Amazon Bedrock knowledge base.

APIs 87
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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning

Amazon Bedrock has recently launched two new capabilities to address these evaluation challenges: LLM-as-a-judge (LLMaaJ) under Amazon Bedrock Evaluations and a brand new RAG evaluation tool for Amazon Bedrock Knowledge Bases.

Metrics 82
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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning

In this post, we propose an end-to-end solution using Amazon Q Business to simplify integration of enterprise knowledge bases at scale. Step Functions orchestrates AWS services like AWS Lambda and organization APIs like DataStore to ingest, process, and store data securely. Delete any skipped resources on the console.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. If you don’t have an existing knowledge base, refer to Create an Amazon Bedrock knowledge base.

APIs 123
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Introducing guardrails in Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). In the following sections, we demonstrate how to create a knowledge base with guardrails.

APIs 131