Category: Amazon Machine Learning

Today, generative artificial intelligence (AI) is at the core of many of the decisions and technologies businesses across the globe are implementing. The linchpin to ensuring that generative AI is effective depends on the foundation models (FMs) storing the data. To make sure that those FMs are pulling the correct data, Amazon Web Services (AWS) has developed a solution through Amazon Bedrock to generate SQL to answer user questions about the data. The solution was developed to support the Federal Institute of São Paulo (IFSP) and has optimized their decision-making.

Amazon Bedrock is now generally available in the Amazon Web Services (AWS) Top Secret cloud. With authority to operate in the AWS Top Secret Cloud, Amazon Bedrock is providing U.S. Government customers with secure access to foundation models (FMs) and generative artificial intelligence (AI) capabilities within AWS’s classified environment.

In this post, we explore how generative artificial intelligence (AI), powered by services such as Amazon Bedrock and Amazon SageMaker, can be harnessed to meet the unique challenges of AWS GovCloud (US). We highlight use cases that demonstrate the potential of generative AI to enhance efficiency, automate workflows, and extract insights—all within a secure, compliant framework.

In today’s fast-paced and competitive business landscape, companies are constantly seeking ways to enhance efficiency, streamline operations, and provide top-notch customer service. Artificial intelligence (AI) has emerged as a powerful tool to help companies achieve these goals while revolutionizing the way they interact with customers. In this post, you can read about the transformative potential of email-based virtual assistants—a standout among AI applications—powered by Amazon Web Services (AWS).

Precise Software Solutions, Inc. (Precise), an Amazon Web Services (AWS) Partner, participated in the AWS Think Big for Small Business Program (TBSB) to expand their AWS capabilities and to grow their business in the public sector. After completion of the program, Precise achieved Advanced tier partner status and was selected by a federal government agency to create a machine learning as a service (MLaaS) platform on AWS. The platform helped the agency gain a four-fold productivity improvement by streamlining and automating labor-intensive manual processes. Read this post to learn more.

Seeking to make access to economic policy documents easier, the Mercatus Center — a university-based research center affiliated with George Mason University — created a generative artificial intelligence (AI) solution. Mercatus developed a platform, QuantGov, with assistance from Amazon Web Services (AWS) resources, including Amazon Bedrock, AWS Lambda, AWS API Gateway, and AWS RDS. Accessible through an interactive AI assistant, the platform provides scalable, accurate, and no-cost access to a treasure trove of data, helping policymakers craft informed public policy that will positively impact people’s lives.

As we look ahead to 2025, it’s crucial to maintain vigilance, especially during the holiday season, when cybersecurity risks tend to escalate. Many organizations use Amazon Web Services (AWS) to enhance their security posture and improve resilience. In this post, we discuss the AWS best practices for securing your data during the holiday season.

Benefit programs like unemployment insurance are complicated and time-sensitive with weekly eligibility requirements. As a result, contact centers routinely experience high call volume that increases exponentially during economic downturns. Yet for many constituents, contact centers are the only lifeline to get the answers they need while looking for work. More than ever, agencies can benefit from AI and automation to reduce call volume, improve self-service, and empower staff productivity—not just to maintain service levels during low unemployment, but to scale and rise to the occasion of unexpected surges in demand.

Healthcare organizations face a significant challenge in making sense of the vast amounts of unstructured medical data trapped in patient records, lab results, and clinical guidelines. Approximately 97 percent of the 50 petabytes (PB) of healthcare data generated annually goes unused. This untapped resource could hold the key to improving patient care and saving valuable clinician time. Read this post learn how we built an innovative solution on Amazon Web Services (AWS) generative artificial intelligence (AI) capabilities that lets clinicians unlock this data treasure trove.

In this post, we showcase a Retrieval-Augmented Generation (RAG) application that can search and query across multiple Indian languages using the Cohere Embed – Multilingual model and Anthropic Claude 3 on Amazon Bedrock. This post focuses on Indian languages, but you can use the approach with other languages that are supported by the large language model.