As Gen AI systems evolve, traditional testing falls short. At Sogeti, we've pioneered a deep, architecture-focused quality engineering framework to ensure AI outputs are reliable, consistent, and ...

Building better AI agents starts with simplicity. Anthropic’s proven patterns help teams move from basic automations to powerful, reliable agentic systems.

Your Kubernetes setup looks perfect—until it fails at 2 AM. Chaos Engineering helps you uncover weaknesses before your users do.

Enterprise AI agents are coming—but without orchestration and governance, chaos will follow. This framework offers clear guidance to deploy agents safely, strategically, and at scale.

The Uniform Information Management Framework (UIMF) reveals the roles your organization already has—but may not have named. It connects context, meaning, data, and technology into a structure that ...

AI agents are redefining migration projects by automating discovery, planning, and execution, easing the strain of limited resources. While not generative AI, these task-focused tools offer ...

This blog provides a structured approach to designing an enterprise-scale landing zone in the cloud. It explores key concepts, design patterns, and security best practices to ensure scalability, ...

The DAMA DMBoK, DCAM, and ISO 38505 frameworks each offer unique strengths for data governance. Understanding their differences helps organizations choose or integrate the best approach for strategic, ...

In recent times, generative AI has transformed the digital landscape, enabling systems to create art, music, and insightful text on demand. However, the conversation is rapidly shifting toward ...

The Architecture Review Board (ARB) ensures that IT changes align with architectural principles, balancing governance with agility. When structured well, it acts as a facilitator rather than a ...

Understanding the difference between implications and consequences is crucial for strategic decision-making. Implications shape long-term outcomes, while consequences are immediate and measurable ...

Data governance plays a critical role in ensuring AI systems are trained on high-quality, unbiased data, driving better performance and ethical outcomes. By establishing frameworks for security, ...