Artificial Intelligence
Category: Customer Solutions
How Infosys Topaz leverages Amazon Bedrock to transform technical help desk operations
In this blog, we examine the use case of a large energy supplier whose technical help desk agents answer customer calls and support field agents. We use Amazon Bedrock along with capabilities from Infosys Topaz™ to build a generative AI application that can reduce call handling times, automate tasks, and improve the overall quality of technical support.
Tyson Foods elevates customer search experience with an AI-powered conversational assistant
In this post, we explore how Tyson Foods collaborated with the AWS Generative AI Innovation Center to revolutionize their customer interaction through an intuitive AI assistant integrated into their website. The AI assistant was built using Amazon Bedrock,
Optimizing Salesforce’s model endpoints with Amazon SageMaker AI inference components
In this post, we share how the Salesforce AI Platform team optimized GPU utilization, improved resource efficiency and achieved cost savings using Amazon SageMaker AI, specifically inference components.
Empowering students with disabilities: University Startups’ generative AI solution for personalized student pathways
University Startups, headquartered in Bethesda, MD, was founded in 2020 to empower high school students to expand their education beyond a traditional curriculum. University Startups is focused on special education and related services in school districts throughout the US. In this post, we explain how University Startups uses generative AI technology on AWS to enable students to design a specific plan for their future either in education or the work force.
PwC and AWS Build Responsible AI with Automated Reasoning on Amazon Bedrock
This post presents how AWS and PwC are developing new reasoning checks that combine deep industry expertise with Automated Reasoning checks in Amazon Bedrock Guardrails to support innovation.
How Amazon scaled Rufus by building multi-node inference using AWS Trainium chips and vLLM
In this post, Amazon shares how they developed a multi-node inference solution for Rufus, their generative AI shopping assistant, using Amazon Trainium chips and vLLM to serve large language models at scale. The solution combines a leader/follower orchestration model, hybrid parallelism strategies, and a multi-node inference unit abstraction layer built on Amazon ECS to deploy models across multiple nodes while maintaining high performance and reliability.
How Indegene’s AI-powered social intelligence for life sciences turns social media conversations into insights
This post explores how Indegene’s Social Intelligence Solution uses advanced AI to help life sciences companies extract valuable insights from digital healthcare conversations. Built on AWS technology, the solution addresses the growing preference of HCPs for digital channels while overcoming the challenges of analyzing complex medical discussions on a scale.
The DIVA logistics agent, powered by Amazon Bedrock
In this post, we discuss how DTDC and ShellKode used Amazon Bedrock to build DIVA 2.0, a generative AI-powered logistics agent.
Pioneering AI workflows at scale: A deep dive into Asana AI Studio and Amazon Q index collaboration
Today, we’re excited to announce the integration of Asana AI Studio with Amazon Q index, bringing generative AI directly into your daily workflows. In this post, we explore how Asana AI Studio and Amazon Q index transform enterprise efficiency through intelligent workflow automation and enhanced data accessibility.
Process multi-page documents with human review using Amazon Bedrock Data Automation and Amazon SageMaker AI
In this post, we show how to process multi-page documents with a human review loop using Amazon Bedrock Data Automation and Amazon SageMaker AI.









