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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Chatbots 116
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. Some components are categorized in groups based on the type of functionality they exhibit. The component groups are as follows. API Gateway is serverless and hence automatically scales with traffic.

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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

We also look into how to further use the extracted structured information from claims data to get insights using AWS Analytics and visualization services. We highlight on how extracted structured data from IDP can help against fraudulent claims using AWS Analytics services. Amazon Redshift is another service in the Analytics stack.

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Boost agent productivity with Salesforce integration for Live Call Analytics

AWS Machine Learning

The Live Call Analytics with Agent Assist (LCA) open-source solution addresses these challenges by providing features such as AI-powered agent assistance, call transcription, call summarization, and much more. Under Available OAuth Scopes , choose Manage user data via APIs (api). We’ve all been there. Choose Save.

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Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation

AWS Machine Learning

At Deutsche Bahn, a dedicated AI platform team manages and operates the SageMaker Studio platform, and multiple data analytics teams within the organization use the platform to develop, train, and run various analytics and ML activities.

APIs 122
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Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

AWS Lake Formation – AWS Lake Formation helps manage data lakes and integrate them with other AWS analytics services. Amazon SageMaker Feature Store – Amazon SageMaker Feature Store allows you to tag your feature groups and search for feature groups using tags. You should take action when resources lack necessary tags.

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Build a foundation model (FM) powered customer service bot with agents for Amazon Bedrock

AWS Machine Learning

The action is an API that the model can invoke from an allowed set of APIs. Action groups are tasks that the agent can perform autonomously. Action groups are mapped to an AWS Lambda function and related API schema to perform API calls. A set of actions comprise an action group.

APIs 110