Category: Amazon Simple Storage Service (S3)

Rideshare demand prediction is a well-explored topic in academia and industry, with abundant online resources offering diverse modeling frameworks tailored to different geographic contexts. A challenge with rideshare demand prediction, however, is that the trip data required to calibrate or train models can be exceptionally large. In this post, we explore the challenges of big data analytics and showcase how ArcGIS GeoAnalytics Engine, a spatial analytics library for the Apache Spark environment, can be used on Amazon EMR to effectively address these problems.

Like many healthcare providers, University Hospitals Coventry and Warwickshire (UHCW) NHS Trust, which manages two major hospitals and serves a population of more than one million, has operated with legacy technology that relies heavily on phone calls and manual processes for contacting patients. Recognizing an opportunity to modernize, the Trust linked up with IBM Consulting for an innovative pilot project to digitize patient engagement channels using Amazon Web Services (AWS). Read this post to learn more.

Acentra Health helps Medicare beneficiaries file quality of care complaints and appeals regarding early hospital discharge or early termination of skilled services. Processing these cases requires meticulous data entry from patient records and forms related to prior authorization notices, patient care, and case management, which often consist of complex medical history. To better support its clients, Acentra Health implemented an intelligent document processing (IDP) solution using Amazon Web Services (AWS). Read this post to learn how their IDP solution reduced document processing times and lowered costs.

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.

Amazon Web Services (AWS) Wickr is an end-to-end encrypted messaging and collaboration service with features designed to keep internal and external communications secure, private, and compliant. In this post, we present an architecture that uses the Wickr messaging solution for protected communication with a generative AI backend system, which uses an existing open source project: the AWS GenAI Chatbot. Read this post to learn more.

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.

Singapore General Hospital (SGH), SingHealth Office of Academic Informatics (OAI), and Amazon Web Services (AWS) collaborated to develop a cost-effective, scalable cloud infrastructure that enables researchers to perform their own analyses on a centrally secured and compliant cloud platform. AWS HealthOmics offers a suite of services that help bioinformaticians, researchers, and scientists to store, query, analyze, and generate insights from genomic and other biological data. Read this post to learn more about the three primary components of HealthOmics used in the solution.

The process of transcribing video or audio files has traditionally been manual and time-consuming. Beyond the need for accurate and cost-effective transcriptions, attorneys have determined a need for timestamping capabilities, speaker identification, search and replace capabilities, the highlighting of specific words, editing capabilities, and most importantly, shortened turnaround times.To address the need for quicker and more accurate transcription of audiovisual files, the Contra Costa County (CCC) District Attorney’s (DA) Office reached out to Amazon Web Services (AWS) and partnered with AWS Partner ScaleCapacity to develop a solution that would automate the manual transcription process. Read this post to learn more.

In this post, we explore how healthcare and life sciences organizations can embrace the data mesh and data as a product (DaaP) principles to unlock the full potential of their health data, drive faster and more efficient drug development, and ultimately, bring life-saving treatments to patients more quickly. We also showcase the Amazon Web Services (AWS) services that support the journey towards effective data management and alignment with data mesh principles.

When government agencies choose Amazon Web Service (AWS) to store data, they choose to take advantage of inheriting the strictest security controls and standards. In addition, AWS services offer a unique opportunity to enhance networking and security approaches, ensuring safe and resilient data transfer mechanisms. This blog post provides guidance towards data sharing among government agencies, offering prescriptive approaches and best practices for implementing secure data exchange solutions using AWS services.