Category: Amazon Bedrock Guardrails

In this blog, learn how five durable pillars—full-stack builders, parallel decision-making, context as a competitive moat, disciplined prioritization, and trust at AI speed—can stabilize your AI product development strategy amid rapid technological change. Drawn from the AWS Product Acceleration team’s work with AI-native product leaders, these principles help organizations cut through the noise and convert AI-driven speed into real customer value rather than chaos.

The methodology described in this post translates subjective personality requirements into testable behaviors, versioned prompts, and documented boundaries. It addresses several dimensions of Responsible AI at AWS, an eight-dimension framework that guides how we build and evaluate AI systems.

This blog share how if your agency is managing millions of unstructured documents, from eligibility records to case files, this post introduces how DMI Document AI, built on Amazon Bedrock, can help you automate document processing, reduce backlogs, and redirect your team toward higher-value mission work.

This post shares how Leidos enhanced ManagedX by adopting multi-agent workflow patterns using the open source Strands Agents SDK, and how AWS Enterprise Support helped guide that evolution.

Every day, the Anne Arundel County, Maryland, Office of Community Engagement and Constituent Services receives hundreds of resident concerns by phone, online, and even in handwritten letters. These aren’t routine inquiries but complex problems, such as zoning disputes, permitting questions, and other issues that residents have escalated to the highest levels of county government. Staff […]

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.

In the age of generative artificial intelligence (AI), data isn’t just king—it’s the entire kingdom. Our previous blog post, Anduril unleashes the power of RAG with enterprise search chatbot Alfred on AWS, highlighted how Anduril Industries revolutionized enterprise search with Alfred, their innovative chat-based assistant powered by Retrieval-Augmented Generation (RAG) architecture. In this post, we examine the technical intricacies that make this system possible.

In this post, you will discover the key challenges public sector agencies face when it comes to real-time data access, and how Amazon Bedrock Agents and Powertools for AWS Lambda work together to address these challenges. The post also includes real-world use cases demonstrating practical applications in the public sector and technical implementation details and best practices.

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.