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Provide live agent assistance for your chatbot users with Amazon Lex and Talkdesk cloud contact center

AWS Machine Learning

For example, the following figure shows screenshots of a chatbot transitioning a customer to a live agent chat (courtesy of WaFd Bank). The associated Amazon Lex chatbot is configured with an escalation intent to process the incoming agent assistance request. The payload includes the conversation ID of the active conversation.

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What Timeframe for an AI Chatbot Project?

Inbenta

Depending on the context in which the chatbot project takes place, and therefore its scope of action, its implementation may take more or less time. Indeed, the development of a chatbot implies creating new jobs such as the one of Botmaster for example. How long does it take to deploy an AI chatbot? Let’s see what these can be.

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Building AI chatbots using Amazon Lex and Amazon Kendra for filtering query results based on user context

AWS Machine Learning

When the user signs in to an Amazon Lex chatbot, user context information can be derived from Amazon Cognito. The Amazon Lex chatbot can be integrated into Amazon Kendra using a direct integration or via an AWS Lambda function. The use of the AWS Lambda function will provide you with fine-grained control of the Amazon Kendra API calls.

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A new look at chatbots

TMP Direct

If you’re looking for ways to spice up your customer service department, then it’s time to look into chatbots. Chatbots have proved their mettle when it comes to simple transactional tasks; and now brands are looking to create interactions that are also memorable and experiential.

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Voicebot vs. Chatbot – what’s the difference?

Babelforce

Voicebot and Chatbot. But when you scratch below the surface, you’ll find that many voicebot definitions sound just like the chatbot definition you already have open in another tab (and vice versa). In this article: Voicebot vs. Chatbot – how different are they? What are Voicebots and Chatbots used for?

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Meet Sophie AI: The Future of Service

TechSee

As a Generative AI enterprise platform, Sophie AI is built to secularly observe, learn and interact at scale, helping your agents, engineers and end-customers. These chatbots demanded a lot of effort from users and administrators. In contrast, Sophie AI is trained like today’s human agents and engineers.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Wipro further accelerated their ML model journey by implementing Wipro’s code accelerators and snippets to expedite feature engineering, model training, model deployment, and pipeline creation. Wipro has used the input filter and join functionality of SageMaker batch transformation API.