Artificial Intelligence

Category: Customer Solutions

Proofpoint Amazon Q Implementation

Unlocking the future of professional services: How Proofpoint uses Amazon Q Business

Proofpoint has redefined its professional services by integrating Amazon Q Business, a fully managed, generative AI powered assistant that you can configure to answer questions, provide summaries, generate content, and complete tasks based on your enterprise data. In this post, we explore how Amazon Q Business transformed Proofpoint’s professional services, detailing its deployment, functionality, and future roadmap.

AI assistant workflow that includes an input guardrail system to enable safe interactions and a government procedures agent to respond to user questions

Meet Boti: The AI assistant transforming how the citizens of Buenos Aires access government information with Amazon Bedrock

This post describes the agentic AI assistant built by the Government of the City of Buenos Aires and the GenAIIC to respond to citizens’ questions about government procedures. The solution consists of two primary components: an input guardrail system that helps prevent the system from responding to harmful user queries and a government procedures agent that retrieves relevant information and generates responses.

Diagram showing data flow between user, Streamlit app, Amazon Bedrock LLM, and Kendra Index

How Amazon Finance built an AI assistant using Amazon Bedrock and Amazon Kendra to support analysts for data discovery and business insights

The Amazon Finance technical team develops and manages comprehensive technology solutions that power financial decision-making and operational efficiency while standardizing across Amazon’s global operations. In this post, we explain how the team conceptualized and implemented a solution to these business challenges by harnessing the power of generative AI using Amazon Bedrock and intelligent search with Amazon Kendra.

Learn how Amazon Health Services improved discovery in Amazon search using AWS ML and gen AI

In this post, we show you how Amazon Health Services (AHS) solved discoverability challenges on Amazon.com search using AWS services such as Amazon SageMaker, Amazon Bedrock, and Amazon EMR. By combining machine learning (ML), natural language processing, and vector search capabilities, we improved our ability to connect customers with relevant healthcare offerings.

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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.