Category: Amazon OpenSearch Service

This post discusses how Amazon Web Services (AWS) can help you set up a unified search platform for educational content using Amazon OpenSearch Service. Amazon OpenSearch Service is a managed service that makes it easy to deploy, operate, and scale OpenSearch clusters in the AWS Cloud. With digital learning becoming increasingly popular, managing a vast amount of educational data can be challenging. A unified search platform enables users to search across multiple indexes at once, providing a centralized view of all available resources.

Curriculum Associates is an education technology (EdTech) company using data-driven technology to bring personalized, evidence-based learning to K12 education institutions. Drawing on the AWS team’s considerable AI expertise and using generative AI resources from AWS, Curriculum Associates transformed their alignment process, freeing up their staff to focus on efforts more directly related to supporting student growth and serving teachers.

Efficiently addressing internal customer support tickets can profoundly impact an organization’s productivity and employee well-being, apart from their ability to focus on the mission at hand. To meet these demands, many nonprofits, such as Thorn, are turning to innovative technology solutions. In this post, we explore how Thorn used Amazon Web Services (AWS) in conjunction with generative artificial intelligence (AI) to revolutionize their internal customer support for organization-wide IT, security, and engineering.

Generative artificial intelligence (AI) can transform the experience of state and local government constituents. With Amazon Lex, you can design and build sophisticated voice and text conversational interfaces, deploy omnichannel experiences with pre-built integrations to contact center solutions, and pay only for speech and text requests with no upfront costs or minimum fees. This post provides a technical walkthrough for building a generative AI chat-based solution.

HolonIQ is a global education intelligence platform that has partnered with Amazon Web Services (AWS) to transform how governments, institutions, and companies access and utilize critical information. By harnessing artificial intelligence (AI) and natural language processing (NLP) technologies, HolonIQ is empowering decision makers in the education, climate tech, and health sectors with instant access to comprehensive, trustworthy data and research. Read this post to learn more.

Healthcare organizations worldwide are leveraging Amazon Web Services (AWS) and partner solutions to modernize, transform, and innovate their businesses. Ensuring the availability and security of critical applications is paramount. For example, two renowned German medical facilities, Fachklinikum Mainschleife and Max Grundig Klinik, needed to modernize their IT infrastructure to comply with stringent regulatory requirements outlined in the country’s Law for Accelerating the Digitalization of Healthcare (DigiG). Reliable and compliant service offerings from AWS enabled the medical facilities to provide reliable access to essential systems.

For years, public health agencies have relied on paper-based case report forms to supplement the electronic laboratory reports (ELRs) they receive for reportable diseases. While ELRs provide positive test results, the accompanying case reports give public health agencies critical clinical, demographic, and risk factor data needed for effective disease investigation and response. However, the sheer volume of COVID-19 cases quickly overwhelmed this manual, paper-based process. Prior to the pandemic, the Office of the National Coordinator for Health IT (ONC) and the Centers for Disease Control and Prevention (CDC) developed standards for an electronic case report (eCR) form that could be automatically sent to public health agencies from providers’ electronic health records (EHRs).

In this post, we will explore the use of generative artificial intelligence (AI) chatbots as a natural language alternative to the service catalog approach. We will present an Amazon Web Services (AWS) architecture pattern to deploy an AI chatbot that can understand user requests in natural language and provide interactive responses to user requests, directing them to the specific systems or services they are looking for. Chatbots simplify the content navigation and discovery process while improving the customer experience.

In this post, we cover an Amazon Web Services (AWS) Cloud infrastructure with a modular architecture that enables you to explore and take advantage of the benefits from different Retrieval-Augmented Generation (RAG)-based generative AI resources in a flexible way. This solution provides several benefits, along with faster time-to-market and shorter development cycles.

The advent of generative artificial intelligence (AI) and large language models (LLMs) present a transformative opportunity to address long-standing educational challenges around creating more personalized learning. In this post, we explain how to implement a personalized, self-paced student companion that addresses the challenges of tailored learning support by harnessing the power of AI to create a personalized, adaptive learning companion that caters to the diverse needs and skillsets of learners.