Cloud, data, and AI in practice.

The Amazon Q Business and Zoom AI Companion integration puts trusted company knowledge inside live meetings. It reduces context switching, respects existing permissions, and helps teams make faster, better decisions.

Generative AI becomes a real competitive advantage when it is grounded in proprietary data, not generic public models. This article explains where foundation models fall short, how fine-tuning and RAG create differentiation, and why a modern data strategy matters as much as the model itself.

Managing or migrating to the cloud is a critical step for many companies, but lean teams often face unpredictable costs, weak governance, and difficulty scaling. With the right strategy, those barriers can become a foundation for growth instead of a brake on it.

Generative AI is moving from proof of concept to operating model. This article outlines the shift to business value, the data foundation required, the main adaptation strategies, and a practical two-phase rollout for internal AI assistants.

Technology is at the center of modern business, but fast growth often leaves companies with complex, poorly documented IT environments. Before migrating to the cloud, adopting AI, or scaling digital operations, you need a clear assessment of where you stand.

For startups, every infrastructure decision can shape the difference between accelerated growth and expensive rework. AWS startup programs offer credits, funding, technical support, and market access that can help teams scale with more confidence.

AI agents are autonomous systems that interpret context, gather data, and act toward a goal. This overview covers their core principles, architecture, common types, business value, adoption risks, and how to apply them responsibly.

Archived guide to AWS Summit Sao Paulo 2025, held on August 13 at the Sao Paulo Expo Center. For the current event page, use Elevata's latest AWS Summit Sao Paulo guide.

AWS gives teams a practical path to build GenAI applications with the right foundation for security, scalability, and responsible adoption, while incentive programs can reduce the cost of experimentation.

Amazon Q Developer Pro can help AWS engineering teams ship faster with more context, better code quality, and stronger governance across modern delivery workflows.