Artificial Intelligence
Category: Customer Solutions
Unleash the power of generative AI with Amazon Q Business: How CCoEs can scale cloud governance best practices and drive innovation
In this post, we share how Hearst, one of the nation’s largest global, diversified information, services, and media companies, overcame these challenges by creating a self-service generative AI conversational assistant for business units seeking guidance from their CCoE.
How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot
Druva enables cyber, data, and operational resilience for thousands of enterprises, and is trusted by 60 of the Fortune 500. In this post, we show how Druva approached natural language querying (NLQ)—asking questions in English and getting tabular data as answers—using Amazon Bedrock, the challenges they faced, sample prompts, and key learnings.
How Planview built a scalable AI Assistant for portfolio and project management using Amazon Bedrock
In this post, we explore how Planview was able to develop a generative AI assistant to address complex work management process by adopting Amazon Bedrock.
Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock
In this post, we learn how SnapLogic’s Agent Creator leverages Amazon Bedrock to provide a low-code platform that enables enterprises to quickly develop and deploy powerful generative AI applications without deep technical expertise.
Generative AI foundation model training on Amazon SageMaker
In this post, we explore how organizations can cost-effectively customize and adapt FMs using AWS managed services such as Amazon SageMaker training jobs and Amazon SageMaker HyperPod. We discuss how these powerful tools enable organizations to optimize compute resources and reduce the complexity of model training and fine-tuning. We explore how you can make an informed decision about which Amazon SageMaker service is most applicable to your business needs and requirements.
Brilliant words, brilliant writing: Using AWS AI chips to quickly deploy Meta LLama 3-powered applications
In this post, we will introduce how to use an Amazon EC2 Inf2 instance to cost-effectively deploy multiple industry-leading LLMs on AWS Inferentia2, a purpose-built AWS AI chip, helping customers to quickly test and open up an API interface to facilitate performance benchmarking and downstream application calls at the same time.
Train, optimize, and deploy models on edge devices using Amazon SageMaker and Qualcomm AI Hub
In this post we introduce an innovative solution for end-to-end model customization and deployment at the edge using Amazon SageMaker and Qualcomm AI Hub.
How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines
In this post, we share how DPG Media is introducing AI-powered processes using Amazon Bedrock into its video publication pipelines. This solution is helping accelerate audio metadata extraction, create a more engaging user experience, and save time.
How SailPoint uses Anthropic’s Claude on Amazon Bedrock to automatically generate TypeScript code for SaaS connectors
In this post, we highlight how the AWS Generative AI Innovation Center collaborated with SailPoint Technologies to build a generative AI-based coding assistant that uses Anthropic’s Claude Sonnet on Amazon Bedrock to help accelerate the development of software as a service (SaaS) connectors.
Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS
In this post, we demonstrate how Intact’s Call Quality solution used Amazon Transcribe and other AWS services to improve critical KPIs with AI-powered contact center call auditing and analytics.









