Category: Amazon Bedrock

This post is a technical deep dive. It explains the Sandbox’s multi-tenant isolation model along with its inherited security and cost controls. It then examines two production-grade multi-agent AIOps systems our teams built on top of it, including the LangGraph (an open source multi-agent orchestration framework) state model, Retrieval-Augmented Generation (RAG) design, OpenSearch query patterns, parallel root cause analysis (RCA) with self-falsification, and the human-in-the-loop safeguards that help make agentic recovery safe in production. Code samples are illustrative and simplified for readability.

In this post, we build on that foundation by constructing specialized AI agents for each data modality along with a supervisor agent that orchestrates cross-modal analysis using Amazon Bedrock AgentCore and Strands Agents SDK. We also train predictive AI models with Amazon SageMaker AI to predict patient outcomes from multimodal features. To further explore the implementation details and get hands-on experience, refer to the accompanying code repository.

In this two-part blog series, we show how you can build agents that interact with multimodal HCLS data, making it easier for end users to query, explore, and ask questions of the data. We build on previous guidance for multimodal data analysis, which demonstrates how to store, query, and analyze clinical, genomic, and medical imaging data using purpose-built AWS services.

Learn more about Engineering Development Hub (EDH), a unified, cloud-based engineering workbench that brings together the applications, compute, and data you need to design, test, and validate complex systems—all in a single, open source environment.

In a previous blog post, we described how AUMOVIO built an AI-powered engineering assistant on Amazon Bedrock that generates automotive-grade embedded code. That system accelerates development

Learn how Peloton uses Amazon Bedrock for access to frontier models, including Anthropic’s Claude Sonnet 4.6, Opus 4.7 and Opus 4.8. Amazon Bedrock also provides global cross-region inference, integration into AWS CloudTrail and AWS CloudWatch, and model access logging for the observability and audit controls its engineering organization requires.

Retailers have always stubbed their toes on early technology adoption—from scanned product barcodes ringing up at the wrong price, to self-checkout lanes that created more shrink than savings, to ecommerce platforms that oversold products they couldn’t ship. But every time, the retailers who learned to master the technology, instead of abandoning it, were the ones who pulled ahead. AI agents are no different.

In this post, we present a deployable reference architecture that addresses both challenges simultaneously. We show how Amazon Bedrock AgentCore orchestrates a single AI agent that reasons across unstructured documents in Amazon S3 and structured data in Snowflake.

Learn how through its strategic partnership with Nasdaq and AWS, BYMA (Bolsas y Mercados Argentinos) went live on Nasdaq’s Eqlipse Clearing platform, hosted on AWS — becoming one of the first FMIs in Latin America to run core clearing and settlement workloads in the cloud.

Learn how financial institutions in Hong Kong face a defining moment in how they deliver technology-driven banking: the Hong Kong Monetary Authority (HKMA) launched Fintech 2030 on November 3, 2025, introducing the DART framework with named initiatives and clear supervisory expectations.