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Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

AWS Machine Learning

Some examples include a customer calling to check on the status of an order and receiving an update from a bot, or a customer needing to submit a renewal for a license and the chatbot collecting the necessary information, which it hands over to an agent for processing. Select the partner event source and choose Associate with event bus.

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GPT-NeoXT-Chat-Base-20B foundation model for chatbot applications is now available on Amazon SageMaker

AWS Machine Learning

This demonstration provides an open-source foundation model chatbot for use within your application. GPT-NeoXT-Chat-Base-20B is designed for use in chatbot applications and may not perform well for other use cases outside of its intended scope. In addition to the aforementioned fine-tuning, GPT-NeoXT-Chat-Base-20B-v0.16

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The Comprehensive Guide to NICE CXone’s Latest AI-Driven Release

Expivia

Key Features: Advanced data analysis for real-time insights Predictive modeling to anticipate customer needs Customizable dashboards for a holistic view of service performance Autopilot: The Next-Gen Virtual Agent Autopilot introduces a level of automation and learning capability that redefines the role of virtual agents in customer service.

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The Next Generation of Service Automation: The Power of Computer Vision

TechSee

VI’s automated insights are natively integrated across the TechSee platform and can be fully integrated into any business application via API. Our text analysis will parse out all relevant texts, and automatically complete their warranty registration for them. . Troubleshooting & Chatbots. Below are a few examples. .

APIs 109
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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Wipro has used the input filter and join functionality of SageMaker batch transformation API. The response is returned to Lambda and sent back to the application through API Gateway. Use QuickSight refresh dataset APIs to automate the spice data refresh. Implement group-based security for dashboard and analysis access control.

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What CTOs Should Know Before Implementing Conversational AI in the Contact Center

SmartAction

It linked via API to internal data sources and current customer input to find a successful solution. Challenges (and Solutions) Conversational AI chatbots can handle a massive number of customer queries at a time, 24/7, many without a need for human intervention. Our virtual agents can solve 80% to 90% of customer problems.

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Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

AWS Machine Learning

Amazon Lex provides the framework for building AI based chatbots. We implement the RAG functionality inside an AWS Lambda function with Amazon API Gateway to handle routing all requests to the Lambda. The Streamlit application invokes the API Gateway endpoint REST API. The API Gateway invokes the Lambda function.

APIs 78