The “Do It Yourself" approach entails that the Total Cost of Ownership of taking an Edge Platform to scale and maintain it, can erode company´s return on investment. Instead, the trend is to collaborate with domain experts and specialized vendors to co-develop solutions for your unique operational challenges. In this article we delve into the pros, cons, and complexities of DIY infrastructure versus pre-built platforms, to help you make an informed decision.

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.

SMPnet’s Optisys software is now available on Barbara’s Marketplace, thanks to a strategic partnership. This collaboration combines SMPnet’s grid optimisation expertise with Barbara’s cybersecure infrastructure, enhancing scalable, low-latency power grid management for greater resilience and efficiency in high renewable energy adoption.

By implementing Barbara's Cybersecure Edge Computing platform, Argos achieved real-time operational control, significant cost reductions, and unlocked scalable solutions across its facilities. Key results included $200,000 in annual fuel savings per plant, a 60% reduction in bandwidth costs, and the ability to deploy new applications on its existing Edge infrastructure. Explore the full story here.

The last 365 days have been another remarkable chapter of innovation, growth, and collective success at Barbara. As 2024 comes to a close, I want to take a moment to express our gratitude to everyone who has been part of Barbara’s incredible journey this year.

Led by Iberdrola, the IA4TES project has successfully completed its three-year initiative (2022–2024), focusing on leveraging Artificial Intelligence to advance renewable energy generation, optimize distribution networks, and enhance customer-level operations. Barbara played a pivotal role by developing industrial edge software to deploy and orchestrate AI at the Edge, enabling smarter, more efficient energy solutions.

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.