AWS Machine Learning Blog

Category: Industries

How Pattern PXM’s Content Brief is driving conversion on ecommerce marketplaces using AI

Pattern is a leader in ecommerce acceleration, helping brands navigate the complexities of selling on marketplaces and achieve profitable growth through a combination of proprietary technology and on-demand expertise. In this post, we share how Pattern uses AWS services to process trillions of data points to deliver actionable insights, optimizing product listings across multiple services.

How Rocket Companies modernized their data science solution on AWS

In this post, we share how we modernized Rocket Companies’ data science solution on AWS to increase the speed to delivery from eight weeks to under one hour, improve operational stability and support by reducing incident tickets by over 99% in 18 months, power 10 million automated data science and AI decisions made daily, and provide a seamless data science development experience.

How Formula 1® uses generative AI to accelerate race-day issue resolution

In this post, we explain how F1 and AWS have developed a root cause analysis (RCA) assistant powered by Amazon Bedrock to reduce manual intervention and accelerate the resolution of recurrent operational issues during races from weeks to minutes. The RCA assistant enables the F1 team to spend more time on innovation and improving its services, ultimately delivering an exceptional experience for fans and partners. The successful collaboration between F1 and AWS showcases the transformative potential of generative AI in empowering teams to accomplish more in less time.

Transforming credit decisions using generative AI with Rich Data Co and AWS

The mission of Rich Data Co (RDC) is to broaden access to sustainable credit globally. Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. In this post, we discuss how RDC uses generative AI on Amazon Bedrock to build these assistants and accelerate its overall mission of democratizing access to sustainable credit.

Accelerate video Q&A workflows using Amazon Bedrock Knowledge Bases, Amazon Transcribe, and thoughtful UX design

The solution presented in this post demonstrates a powerful pattern for accelerating video and audio review workflows while maintaining human oversight. By combining the power of AI models in Amazon Bedrock with human expertise, you can create tools that not only boost productivity but also maintain the critical element of human judgment in important decision-making processes.

How Travelers Insurance classified emails with Amazon Bedrock and prompt engineering

In this post, we discuss how FMs can reliably automate the classification of insurance service emails through prompt engineering. When formulating the problem as a classification task, an FM can perform well enough for production environments, while maintaining extensibility into other tasks and getting up and running quickly. All experiments were conducted using Anthropic’s Claude models on Amazon Bedrock.

The following diagram illustrates the workflow of patch-level prediction tasks on a WSI

Accelerate digital pathology slide annotation workflows on AWS using H-optimus-0

In this post, we demonstrate how to use H-optimus-0 for two common digital pathology tasks: patch-level analysis for detailed tissue examination, and slide-level analysis for broader diagnostic assessment. Through practical examples, we show you how to adapt this FM to these specific use cases while optimizing computational resources.

quantiles

Solve forecasting challenges for the retail and CPG industry using Amazon SageMaker Canvas

In this post, we show you how Amazon Web Services (AWS) helps in solving forecasting challenges by customizing machine learning (ML) models for forecasting. We dive into Amazon SageMaker Canvas and explain how SageMaker Canvas can solve forecasting challenges for retail and consumer packaged goods (CPG) enterprises.

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

This post introduces HCLTech’s AutoWise Companion, a transformative generative AI solution designed to enhance customers’ vehicle purchasing journey. In this post, we analyze the current industry challenges and guide readers through the AutoWise Companion solution functional flow and architecture design using built-in AWS services and open source tools. Additionally, we discuss the design from security and responsible AI perspectives, demonstrating how you can apply this solution to a wider range of industry scenarios.

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

In this post, we show how you can use our enterprise graph machine learning (GML) framework GraphStorm to solve prediction challenges on large-scale complex networks inspired by our practices of exploring GML to mitigate the AWS backbone network congestion risk.