Accountability, APIs and Automotive - Customer Contact Central

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

NOVEMBER 7, 2024

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. Although the principles discussed are applicable across various industries, we use an automotive parts retailer as our primary example throughout this post.

APIs

APIs Enterprise Automotive Customer Support

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning

MARCH 19, 2025

Note that these APIs use objects as namespaces, alleviating the need for explicit imports. API Gateway supports multiple mechanisms for controlling and managing access to an API. AWS Lambda handles the REST API integration, processing the requests and invoking the appropriate AWS services.

APIs

APIs Automotive Accountability Analytics

Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

MARCH 27, 2025

Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API. Test the code using the native inference API for Anthropics Claude The following code uses the native inference API to send a text message to Anthropics Claude. client = boto3.client("bedrock-runtime",

Education

Education Engineering APIs Enterprise

Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

MAY 1, 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.

Chatbots

Chatbots APIs Engineering Automotive

Amazon Rekognition Labels adds 600 new labels, including landmarks, and now detects dominant colors

AWS Machine Learning

NOVEMBER 21, 2022

The following table shows the labels and confidence scores returned in the API response. Vehicles and automotive – Truck, Wheel, Tire, Bumper, Car Seat, Car Mirror, etc. By default, the API returns up to 10 dominant colors unless you specify the number of colors to return. Confidence Scores. Brooklyn Bridge. Improved labels.

APIs

APIs Advertising Automotive Personalization

Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS

AWS Machine Learning

JULY 3, 2023

Then, using the SageMaker API, we can start the asynchronous inference job as follows: import glob import time max_images = 10 input_locations,output_locations, = [], [] for i, file in enumerate(glob.glob("data/processedimages/*.png")): A list of models is available in the models_manifest.json file provided by JumpStart.

Calibration

Calibration APIs Scripts Automotive

Get insights on your user’s search behavior from Amazon Kendra using an ML-powered serverless stack

AWS Machine Learning

MAY 25, 2023

Prerequisites Complete the following prerequisite steps: If you’re a first-time user of QuickSight in your AWS account, sign up for QuickSight. Get insights from Amazon Kendra search metrics We can get the metrics data from Amazon Kendra using the GetSnapshots API. Please try out the solution and let us know your feedback.

Automotive

Automotive Metrics Analytics APIs

Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning

NOVEMBER 22, 2023

In this innovation talk, hear how the largest industries, from healthcare and financial services to automotive and media and entertainment, are using generative AI to drive outcomes for their customers. This session uses the Claude 2 LLM as an example of how prompt engineering helps to solve complex customer use cases. Reserve your seat now!

Engineering

Engineering Best practices APIs Government

Best prompting practices for using Meta Llama 3 with Amazon SageMaker JumpStart

AWS Machine Learning

SEPTEMBER 12, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. Meta Llama 3 inference parameters For Meta Llama 3, the Messages API allows you to interact with the model in a conversational way.

Engineering

Engineering Automotive Best practices Enterprise

Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

AWS Machine Learning

OCTOBER 5, 2022

Apache Flink is a distributed streaming, high-throughput, low-latency data flow engine that provides a convenient and easy way to use the Data Stream API, and it supports stateful processing functions, checkpointing, and parallel processing out of the box. Yash Shah is a Science Manager in the Amazon ML Solutions Lab.

Calibration

Calibration Engineering Automotive Analytics

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

AUGUST 2, 2023

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. After ingestion, images can be searched via the Amazon Kendra search console, API, or SDK. However, we can use CDE for a wider range of use cases.

Enterprise

Enterprise Healthcare APIs Big data

Enable predictive maintenance for line of business users with Amazon Lookout for Equipment

AWS Machine Learning

MARCH 28, 2023

Prerequisites All you need to get started is an AWS account and a history of sensor data for assets that can benefit from a predictive maintenance approach. The sensor data should be stored as CSV files in an Amazon Simple Storage Service (Amazon S3) bucket from your account. There are no constraints on the evaluation range.

Accountability

Accountability APIs Engineering Enterprise

Welcome to a New Era of Building in the Cloud with Generative AI on AWS

AWS Machine Learning

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. With Amazon Bedrock, customers are only ever one API call away from a new model.

APIs

APIs Enterprise Best practices Technology

Simplify automotive damage processing with Amazon Bedrock and vector databases

AWS Machine Learning

NOVEMBER 14, 2024

In the automotive industry, the ability to efficiently assess and address vehicle damage is crucial for efficient operations, customer satisfaction, and cost management. By combining these powerful tools, we have developed a comprehensive solution that streamlines the process of identifying and categorizing automotive damage.

Automotive

Automotive Engineering APIs Management

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

AWS Machine Learning

MARCH 5, 2025

Was there an inadvertent breaking change in recent API changes? Infrastructure Tool The Infrastructure Tool uses CloudTrail data to analyze critical control-plane events, such as configuration changes, security group updates, or API calls. A sharp decrease in the number of successful invocations of the Remote Vehicle Management API.

APIs

APIs Engineering Automotive Metrics

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning

JANUARY 29, 2025

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. Prerequisites You should have the following prerequisites: An AWS account with access to Amazon Bedrock. For more information, see Create a service role for model import.

APIs

APIs Benchmark Automotive Enterprise

Discover insights with the Amazon Q Business Microsoft Teams connector

AWS Machine Learning

NOVEMBER 11, 2024

If you don’t have Microsoft user account yet, see Add users and assign licenses at the same time. Create a Microsoft Teams account in Microsoft 365. Add necessary permissions: In the API Permissions section of your application page, choose Add a Permission. Next, prepare the Microsoft 365 tenant ID and OAuth 2.0

APIs

APIs Accountability Automotive Enterprise

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

AWS Machine Learning

JANUARY 7, 2025

These managed agents play conductor, orchestrating interactions between FMs, API integrations, user conversations, and knowledge bases loaded with your data. If the user request invokes an action, action groups configured for the agent will invoke different API calls, which produce results that are summarized as the response to the user.

Chatbots

Chatbots Management Best practices APIs

Deploy DeepSeek-R1 distilled Llama models with Amazon Bedrock Custom Model Import

AWS Machine Learning

JANUARY 29, 2025

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. Prerequisites You should have the following prerequisites: An AWS account with access to Amazon Bedrock. For more information, see Create a service role for model import.

APIs

APIs Benchmark Automotive Enterprise

Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics

AWS Machine Learning

MARCH 7, 2025

Improving data-driven decision-making in automotive manufacturing An international auto company manages a large dataset, supporting thousands of use cases across engineering, manufacturing, and customer service. Conclusion In this post, we discussed how to get started with Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune.

Analytics

Analytics Automotive Best practices Construction

Customer Contact Central

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

Trending Sources

Generate training data and cost-effectively train categorical models with Amazon Bedrock

Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

Amazon Rekognition Labels adds 600 new labels, including landmarks, and now detects dominant colors

Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS

Get insights on your user’s search behavior from Amazon Kendra using an ML-powered serverless stack

Your guide to generative AI and ML at AWS re:Invent 2023

Best prompting practices for using Meta Llama 3 with Amazon SageMaker JumpStart

Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Enable predictive maintenance for line of business users with Amazon Lookout for Equipment

Welcome to a New Era of Building in the Cloud with Generative AI on AWS

Simplify automotive damage processing with Amazon Bedrock and vector databases

Innovating at speed: BMW’s generative AI solution for cloud incident analysis

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

Discover insights with the Amazon Q Business Microsoft Teams connector

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

Deploy DeepSeek-R1 distilled Llama models with Amazon Bedrock Custom Model Import

Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics

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