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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.

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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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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.

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Accelerate video Q&A workflows using Amazon Bedrock Knowledge Bases, Amazon Transcribe, and thoughtful UX design

AWS Machine Learning

The transcript gets postprocessed into a text form more appropriate for use by an LLM, and an AWS Step Functions state machine syncs the transcript to a knowledge base configured in Amazon Bedrock Knowledge Bases. If you are looking for a sample video, consider downloading a TED talk.

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The SaaS Guide to Customer Engagement, Retention, and Advocacy

After onboarding, most SaaS customers have to find their own way to success—with little more than a few CSM calls (if they’re a large enough account to have one), and a knowledge base to get them there.

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Adobe enhances developer productivity using Amazon Bedrock Knowledge Bases

AWS Machine Learning

To address these challenges, Adobe partnered with the AWS Generative AI Innovation Center , using Amazon Bedrock Knowledge Bases and the Vector Engine for Amazon OpenSearch Serverless. Using Amazon Bedrock Knowledge Bases, we created a customized, fully managed solution that improved the retrieval effectiveness.

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

AWS Machine Learning

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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Leadership Panel: Lessons Learnt from a Global Support Community

Speaker: Panel hosted by Adrian Speyer, Head of Community, Vanilla Forums

Join us to learn: How to integrate your knowledge base (and KCS) with your community. Vanilla’s Head of Community, Adrian Speyer leads the panel to uncover and discuss their common initiatives and their individual journeys to success. How to establish a successful ambassador program.

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6 Killer Applications for Artificial Intelligence in the Customer Engagement Contact Center

If Artificial Intelligence for businesses is a red-hot topic in C-suites, AI for customer engagement and contact center customer service is white hot. This white paper covers specific areas in this domain that offer potential for transformational ROI, and a fast, zero-risk way to innovate with AI.