Remove resources product-updates
article thumbnail

Manage your Amazon Lex bot via AWS CloudFormation templates

AWS Machine Learning

Managing your Amazon Lex bots using AWS CloudFormation allows you to create templates defining the bot and all the AWS resources it depends on. AWS CloudFormation provides and configures those resources on your behalf, removing the risk of human error when deploying bots to new environments. Resources: # 1.

article thumbnail

WFM: The Missing Link in Your Strategic Vision

CCNG

By being at the forefront of operations, we can identify opportunities to drive efficiencies, cut costs, and optimize resources. Happier agents lead to improved customer experiences, reduced turnover, and increased productivity. And that’s a strategic advantage!

CCNG 195
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Enterprise Contact Center Solutions: A Game Changer

NobelBiz

At the core of this modern transformation lie Enterprise Contact Center Solutions , sophisticated platforms designed to streamline communication, enhance productivity, and drive customer satisfaction. WFM also helps reduce labor costs by efficiently allocating resources based on demand forecasts and agent availability.

article thumbnail

Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions

AWS Machine Learning

Upon submission, the Streamlit web application updates an Amazon DynamoDB table with image details. The DynamoDB update triggers an AWS Lambda function, which starts a Step Functions workflow. Updates the image status in a DynamoDB table. Updates the image status in a DynamoDB table.

APIs 116
article thumbnail

Live Meeting Assistant with Amazon Transcribe, Amazon Bedrock, and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. Do not use this solution to stream, record, or transcribe calls if otherwise prohibited. The stacks take about 35–40 minutes to deploy.

APIs 107
article thumbnail

Amazon SageMaker simplifies setting up SageMaker domain for enterprises to onboard their users to SageMaker

AWS Machine Learning

As a platform administrator, you can use the updated user interface (UI) and APIs to onboard users faster, with the right security settings and infrastructure. For SageMaker Studio , select the updated or classic version. Let’s explore some newly launched features as part of this setup that allow updates to existing domains.

article thumbnail

Introducing automatic training for solutions in Amazon Personalize

AWS Machine Learning

Prerequisites To enable automatic training for your solutions, you first need to set up Amazon Personalize resources. For more information about tagging Amazon Personalize resources, see Tagging Amazon Personalize resources. Technical Product Manager working with AWS AI/ML on the Amazon Personalize team.