Category: Database

In the modern manufacturing environment, Product Lifecycle Management (PLM) systems have become essential for competitive advantage. By establishing a single source of truth for product data from initial design through manufacturing, service, and end-of-life, PLM enables manufacturers to make faster decisions, reduce errors, and bring products to market more quickly. For manufacturers using Siemens Teamcenter […]

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.

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.

This blog post introduces a serverless dynamic pricing platform built on Amazon Web Services (AWS) that helps restaurants automatically adjust menu prices based on real-time demand patterns. The solution enables restaurants to maximize revenue during peak hours while attracting price-sensitive customers during slower periods.

Across R&D organizations, AI agents are beginning to design molecules, plan syntheses, execute assays, and analyze experimental data. But these systems often operate without awareness of prior experiments, failed approaches, or parallel work happening across the organization. In this blog, learn how Sanofi recognized this limitation early and partnered with Amazon Web Services (AWS) to reimagine the foundation for AI-enabled discovery.

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.

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.

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.

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.