Category: Amazon Simple Storage Service (S3)

In this post you will explore how finance and actuarial teams can find a balance between the ability to scale models and to experiment with changes. AWS InsuranceLake accelerator solution will be used ingest commercial auto and workers compensation policy data containing written premiums and enrich it with calculated earned monthly premiums using an Excel spreadsheet-based model that has been turned into an API and made enterprise grade with Coherent Spark on AWS.

BMW Group is building toward Industry AI on Amazon SageMaker AI by fine-tuning task-specific LoRA adapters on engineering process data and serving multiple domain capabilities from a single endpoint. Large language models (LLMs) produce convincing output on general tasks, but company-internal engineering processes, proprietary taxonomies, and domain-specific quality standards aren’t represented in public training corpora. Prompting with rules and examples doesn’t reliably close this gap when a task imposes many hard constraints simultaneously because the model has no training signal telling it which constraints are inviolable. In this post, we describe the architecture, walk through the results, and present a repeatable framework you can apply to your own domain.

In this post, we summarize what HHS has proposed, when it is likely to matter, and how to use Amazon Web Services (AWS) to close the gaps now. We cover how AWS Backup maps to the three proposed backup and recovery obligations, and we introduce the HIPAA Assistant, an open source sample from AWS that reviews your infrastructure-as-code and application code for Security Rule gaps and cites each finding to the exact paragraph of the regulation.

Automotive firmware teams face a structural bottleneck: physical electronic control unit (ECU) hardware doesn’t scale at the pace of software development. Waiting for hardware access creates delayed test cycles, late defect detection, and limited parallel coverage across Software Defined Vehicle (SDV) programs.

In this post, we show how Santos modernized its subsurface computing environment on AWS: moving from distributed on-premises infrastructure to a centralized, cloud-based platform that delivers high performance computing (HPC), high performance storage, and secure remote visualization for more than 200 geoscientists across Australia.

In this post, we explore how Celfocus, an Amazon Web Services (AWS) Partner specializing in digital transformation for the telecommunications industry, built an automated Change Impact Analysis solution in collaboration with Fastweb+Vodafone, one of Italy’s leading telecommunications operators.

In this post, we deliver the implementation blueprint. We walk through the complete reference architecture built on Amazon Web Services (AWS), break down the layer service topology, detail the multi-agent orchestration pattern using Amazon Bedrock AgentCore and the Strands Agents SDK.

This post documents a working system. Five KYC/KYB checks, each with its own agent architecture, prompt methodology, and failure modes. We built it, ran it, broke it, fixed it, and are publishing the full method so you can build your own.

This post demonstrates on Massive Multitask Language Understanding (MMLU) [Hendrycks et al., 2021], an open-source multiple-choice benchmark accessible via Hugging Face Hub, selecting four business-relevant subjects.

This is part 3 of our three-part series on how Amazon Web Services (AWS) aligns with MPA Content Security Best Practices with a particular focus on media archives.