APIs and industry solution - Customer Contact Central

Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

OCTOBER 21, 2024

This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API. Having a unified developer experience when accessing custom models or base models through Amazon Bedrock’s API. Ease of deployment through a fully managed, serverless, service. 2, 3, 3.1,

APIs

APIs Scripts Finance Real estate

Automate cloud security vulnerability assessment and alerting using Amazon Bedrock

AWS Machine Learning

NOVEMBER 18, 2024

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, 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.

APIs

APIs Accountability Engineering Enterprise

Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

SEPTEMBER 6, 2023

These SageMaker endpoints are consumed in the Amplify React application through Amazon API Gateway and AWS Lambda functions. To protect the application and APIs from inadvertent access, Amazon Cognito is integrated into Amplify React, API Gateway, and Lambda functions.

Enterprise

Enterprise APIs Real estate Construction

Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

AUGUST 21, 2024

We also explore best practices for optimizing your batch inference workflows on Amazon Bedrock, helping you maximize the value of your data across different use cases and industries. Solution overview The batch inference feature in Amazon Bedrock provides a scalable solution for processing large volumes of data across various domains.

Call Center

Call Center APIs Engineering Accountability

Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

FEBRUARY 6, 2024

Using the job ID and message ID returned by the previous request, the client connects to the WebSocket API and sends the job ID and message ID to the WebSocket connection. A Lambda function invokes the Amazon Textract API DetectDocument to parse tabular data from source documents and stores extracted data into DynamoDB.

Government

Government APIs industry solution Education

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

JANUARY 5, 2024

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. It helped enrich the scoring data for better decision making.

Management

Management APIs Engineering Government

Build an agronomic data platform with Amazon SageMaker geospatial capabilities

AWS Machine Learning

DECEMBER 1, 2022

These differences in satellite images and frequencies also lead to differences in API capabilities and features. These web and mobile applications, however, need to consume and quickly display processed imagery and agronomic insights via APIs. In his free time, he enjoys hiking, travelling, and spending time with family and friends.

APIs

APIs Analytics Engineering Technology

Streamline Sales Processes with Enterprise CPQ

Cincom

MAY 8, 2024

Integration with Existing Systems: APIs facilitate data sharing between CPQ and other core platforms like CRM, ERP, accounting, e-commerce, and more. Automated Document Generation: CPQ software produces professional quote documentation tailored to the products selected.

Enterprise

Enterprise Sales CRM Upselling

Large-scale revenue forecasting at Bosch with Amazon Forecast and Amazon SageMaker custom models

AWS Machine Learning

SEPTEMBER 23, 2022

Bosch is a multinational corporation with entities operating in multiple sectors, including automotive, industrial solutions, and consumer goods. The neural forecasters can be bundled as a single ensemble model, or incorporated individually into Bosch’s model universe, and accessed easily via REST API endpoints.

APIs

APIs Metrics Automotive Engineering

Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

FEBRUARY 13, 2023

References More information is available at the following resources: Automate Amazon SageMaker Studio setup using AWS CDK AWS SageMaker CDK API reference About the Authors Zdenko Estok works as a cloud architect and DevOps engineer at Accenture. Shikhar enjoys playing guitar, composing music, and practicing mindfulness in his spare time.

Scripts

Scripts Best practices Transportation Construction

Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

NOVEMBER 1, 2022

For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. The Step Functions state machine, S3 bucket, Amazon API Gateway resources, and Lambda function codes are stored in the GitHub repo. The following figure illustrates our Step Function workflow.

Engineering

Engineering APIs Accountability industry solution

Multilingual content processing using Amazon Bedrock and Amazon A2I

AWS Machine Learning

NOVEMBER 13, 2024

It uses Amazon Bedrock through the Boto3 API to use Anthropic’s Claude V3 multi-modal language models, but makes it straightforward to use file formats that are otherwise not supported by Anthropic’s Claude models. A predefined JSON schema can be provided to the Rhubarb API, which makes sure the LLM generates data in that specific format.

APIs

APIs Accountability industry solution Management

Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

SEPTEMBER 18, 2024

Instructions – The following are some examples from the design instructions: Header Design: - Choose an attention-grabbing background color and font that aligns with the client's industry. For this post, we use Anthropic’s Claude models on Amazon Bedrock.

Personalization

Personalization Construction Consulting Consulting

Bring SageMaker Autopilot into your MLOps processes using a custom SageMaker Project

AWS Machine Learning

JUNE 14, 2023

For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. Shikhar aids in architecting, building, and maintaining cost-efficient, scalable cloud environments for the organization, and supports the GSI partner in building strategic industry solutions on AWS.

Best practices

Best practices Scripts Education Engineering

Customer Contact Central

Amazon Bedrock Custom Model Import now generally available

Automate cloud security vulnerability assessment and alerting using Amazon Bedrock

Trending Sources

Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

Accenture creates a regulatory document authoring solution using AWS generative AI services

Modernizing data science lifecycle management with AWS and Wipro

Build an agronomic data platform with Amazon SageMaker geospatial capabilities

Streamline Sales Processes with Enterprise CPQ

Large-scale revenue forecasting at Bosch with Amazon Forecast and Amazon SageMaker custom models

Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

Automated exploratory data analysis and model operationalization framework with a human in the loop

Multilingual content processing using Amazon Bedrock and Amazon A2I

Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

Bring SageMaker Autopilot into your MLOps processes using a custom SageMaker Project

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