Industry at the Edge posts

By 2025, analysts predict that 50% of enterprises will have adopted edge computing, up from just 20% in 2024. At Barbara, we’ve seen this momentum firsthand, with inquiries about Edge Computing and AI increasing fourfold in 2024 alone. While the potential of Edge AI is undeniable, its widespread adoption brings both opportunities and challenges. In this post, we dive into key predictions for Edge AI in 2025 and examine the challenges the industry must overcome to unlock its full potential.

This post explores how Barbara’s MLOps capabilities simplify the remote deployment of AI models — like ResNet18 — to edge devices, all managed effortlessly through a single, intuitive console. Discover how easy edge AI deployment can be.

Our recent webinar with UAO featured a live demonstration of Barbara’s platform in action, showcasing how Schneider’s SoftdPAC runtimes can be deployed across multiple industrial PCs, regardless of the hardware manufacturer, all managed remotely from a centralized platform developed by Barbara.

Deploying machine learning models across multiple locations is becoming critical for scaling AI. Whether you're building infrastructure or serving diverse clients, this guide covers key strategies, challenges, and best practices for successful multi-site model deployment.

According to Gartner, 13% of organizations implementing IoT projects are already leveraging digital twins, while another 62% are actively planning or developing them. Yet, industries like energy, water infrastructure, and process manufacturing face significant hurdles in adopting these powerful solutions. This article delves into potential strategies to overcome these challenges.

When I first joined Barbara as People Manager, I was eager to see how the company's values would play out in our daily operations. It’s one thing to talk about culture, but experiencing it firsthand is quite another. This is my experience