.png)
AI agents are becoming practical tools that autonomously perform tasks, support decision-making, and adapt to business needs. By starting with focused, high-value use cases and ensuring strong data governance and human oversight, organizations can unlock real value while building long-term capability.
A data-centric approach to AI prioritizes improving data quality over tweaking models or code. As AI shifts toward unstructured data like text and images, traditional tools fall short. Data and analytics architects can address these challenges using four key pillars: data preparation and exploratory analysis, feature engineering, data labeling and annotation, and data augmentation. These pillars enable the creation of high-quality, AI-ready datasets, enhanced by modern tools like automation, low-code platforms, and synthetic data generation for scalable, intelligent systems.
A big side effect of the world's new focus on work from home? Collaboration delivers leverage. Those of us who do software for a living are quite fortunate. Many of the habits we've learned in…
I suspect that when the legendary Ward Cunningham coined the term "technical debt", it did not take him long to realize he'd created a monster: "I am in favor of writing code to reflect your…
In SaaS, technical debt isn’t a bug, it's a feature – it’s a feature of creativity and velocity. People are writing more code to solve more problems than ever before. Of course, they are not…
For chronic disease sufferers – often already under medical care – data-driven personalized medicine provides a promising new application for tailored therapies and disease management. Today, the right combination of technology infrastructure, advanced AI technology…
If your plan for cloud computing is to simply “move to the cloud”, it's time to rethink your plan. Success is not about “moving”; it's about changing to cloud computing. Everyone wants the business and…
Are your cloud and application stack well architected? Probably not. And that’s OK. Cloud architects inside Amazon originated the AWS Well-Architected Framework (aka "Well-Architected"), and announced it in 2015. It aspired to set guidelines and…
The AWS Partner Network (APN) has now certified CloudGeometry as a Designated Service Provider for Amazon Redshift, the fastest-growing cloud data Warehouse offering. This recognition is the fourth such...
Building our on successful collaboration with a broad spectrum of SaaS companies and corporate innovators, CloudGeometry now been recognized with a certification by AWS APN as a Designated Service Provider for AWS Lambda Services. This added recognition...
Almost any piece of industrial equipment today produces its own rich and steady stream of data. Digital diagnostics embedded in devices help with on-site troubleshooting when dispatching a trained local technician. But what about extending…
The AWS Partner Network (APN) has endorsed ElevationData, the CloudGeometry company specializing in data engineering and data science pipelines, as a Designated Service Provider...
We are proud to announce that the AWS Partner Network (APN) has certified us as a Designated Service Provider for AWS Database Migration Services. These AWS credentials...
By now, the consensus view of Big Data is that bigger doesn’t translate into better. It’s a more subtle irony that in the face of bigger and faster data, data science is still vexingly difficult...
CloudGeometry, CEO
:
"In today's rapidly evolving business landscape, understanding the fundamentals of AI Agents is no longer optional for leaders".
