Category: Analytics

Emerging sustainability reporting requirements demand standardized, auditable processes with flexibility to adapt to evolving frameworks. For many organizations, the challenge isn’t data availability, it’s synthesizing fragmented information into coherent, audit-ready disclosures. Sustainability data resides across facility management systems, procurement platforms, HR tools, carbon accounting solutions, and operational databases. Many traditional business intelligence tools are not […]

In this blog, we provide a practitioner-focused guide for enabling a new AWS Region in a financial services enterprise AWS environment. We walk through each workstream, from initial governance approval through networking, security, operations, and workload readiness, highlighting the considerations, dependencies, and common pitfalls that teams encounter.

In this post, we show how you can use AWS HealthLake to meet CMS-0057-F requirements while building a FHIR data solution that accelerates your broader digital transformation.

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.

When AWS released Amazon S3 Tables, this calculus changed. In this post, you will learn how Amica reduced their ETL job runtimes by 80% by building a data lake for core insurance data using S3 Tables.

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.

Every Thanksgiving, tens of thousands of Peloton Members log on for Turkey Burn, a community tradition that has grown into one of the most technically demanding real-time workloads in the fitness industry. In 2024 and 2025, that engineering foundation held flawlessly: two consecutive events, zero major incidents. This builds on a 2023 Guinness World Record that saw 27,556 simultaneous participants in a single cycling class. Behind those results is a sophisticated cloud architecture on AWS, shaped by years of rigorous engineering, deep partnership between Peloton and AWS teams, and a relentless commitment to continuous improvement.

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.