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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Numerous customers face challenges in managing diverse data sources and seek a chatbot solution capable of orchestrating these sources to offer comprehensive answers. This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment.

Chatbots 121
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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning

With recent advances in large language models (LLMs), a wide array of businesses are building new chatbot applications, either to help their external customers or to support internal teams. Also, note the physical ID of the API Gateway connection, which should look something like zxpdjtklw2 , as shown in the following screenshot.

Chatbots 120
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Streamline workflow orchestration of a system of enterprise APIs using chaining with Amazon Bedrock Agents

AWS Machine Learning

Intricate workflows that require dynamic and complex API orchestration can often be complex to manage. In this post, we explore how chaining domain-specific agents using Amazon Bedrock Agents can transform a system of complex API interactions into streamlined, adaptive workflows, empowering your business to operate with agility and precision.

APIs 127
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Integrate dynamic web content in your generative AI application using a web search API and Amazon Bedrock Agents

AWS Machine Learning

These agents help users complete actions based on organizational data and user input, orchestrating interactions between foundation models (FMs), data sources, software applications, and user conversations. Amazon Bedrock Agents offers developers the ability to build and configure autonomous agents in their applications.

APIs 102
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DXC transforms data exploration for their oil and gas customers with LLM-powered tools

AWS Machine Learning

Data-driven insights can accelerate the process of identifying potential locations and improve decision-making. In this post, we show you how DXC and AWS collaborated to build an AI assistant using large language models (LLMs), enabling users to access and analyze different data types from a variety of data sources.

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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Modern chatbots can serve as digital agents, providing a new avenue for delivering 24/7 customer service and support across many industries. Chatbots also offer valuable data-driven insights into customer behavior while scaling effortlessly as the user base grows; therefore, they present a cost-effective solution for engaging customers.

Chatbots 111
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AI in Customer Service: Chatbots and ChatGPT are just the Start

TechSee

While initial conversations now focus on improving chatbots with large language models (LLMs) like ChatGPT, this is just the start of what AI can and will offer. Deploying this AI will require more than simply upgrading a chatbot. AI is rapidly becoming a critical tool in customer service.

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