Remove Accountability Remove Customer Support Remove Knowledge Base
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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 129
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Build a self-service digital assistant using Amazon Lex and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Organizations strive to implement efficient, scalable, cost-effective, and automated customer support solutions without compromising the customer experience. You can simply connect QnAIntent to company knowledge sources and the bot can immediately handle questions using the allowed content. Create an Amazon Lex bot.

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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Generative AI solutions often use Retrieval Augmented Generation (RAG) architectures, which augment external knowledge sources for improving content quality, context understanding, creativity, domain-adaptability, personalization, transparency, and explainability.

APIs 102
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Improve AI assistant response accuracy using Knowledge Bases for Amazon Bedrock and a reranking model

AWS Machine Learning

Most common use cases for chatbot assistants focus on a few key areas, including enhancing customer experiences, boosting employee productivity and creativity, or optimizing business processes. For instance, customer support, troubleshooting, and internal and external knowledge-based search. Scott Fitzgerald.

APIs 132
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Guest Blog: Why Knowledge Base Integration with Live Chat Is Important for Better Customer Support

ShepHyken

This week on our Friends on Friday guest blog post my colleague, Jason Grills, writes about the importance of good customer support and the impact it can have on your business. Customer support agents must understand just how important their roles and responsibilities are to the customer experience. Shep Hyken.

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Automate the insurance claim lifecycle using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

They can enhance operational efficiency, customer service, and decision-making while reducing costs and enabling innovation. These agents excel at automating a wide range of routine and repetitive tasks, such as data entry, customer support inquiries, and content generation.

APIs 139
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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

Generative AI has transformed customer support, offering businesses the ability to respond faster, more accurately, and with greater personalization. AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses.

APIs 128