Industry at the Edge posts

Industrial digitalization has become unnecessarily complex, with AI-first strategies before they even get started. In this article, we explore a simpler approach: start by connecting one machine, collecting one stream of data, building one dashboard, or automating one workflow. Because starting small is often the smartest way.

Every industrial company today is looking for the same profile: someone who understands machines, networks, data, cloud, and AI. Someone who can connect a PLC, deploy a container, troubleshoot a VPN, and explain why the data pipeline is broken. And... surprise, surprise... they can't find it. In this article we explain why.

Many industrial companies have a data strategy, yet very few can honestly say their business is better because it. The reason often isn’t technology or talent, but a missing piece in what we call the Triangle of Digitalization — a simple framework that reveals why most data strategies quietly fail.

Remote mines can’t depend on the cloud. Edge AI processes data on-site, enabling real-time insights, less downtime, and smarter autonomous operations. It’s becoming the backbone of digital mining.

Discover why Kubernetes struggles at the industrial edge and how edge-native platforms like Barbara deliver resilience, security, and faster ROI.

As industrial operations grow more distributed and data-driven, cybersecurity must keep up. The old model stacking specialized hardware in datacenters, is fast becoming obsolete. In this article, we explore virtualized cybersecurity as a strategic game-changer, especially for sectors like oil & gas, utilities, and manufacturing.