Welcome to our blog where we dive deep into the philosophy of simplicity in an increasingly complex world
Outlining the key steps to prepare your business for automation: review and streamline your current processes, set clear goals, document everything, and start with simple, repetitive tasks. Involve your team early, choose the right tools and partners (like ETT), and begin with a small pilot before scaling up. Continuous improvement and good change management are essential for long-term success.
At UiPath on Tour London 2025, Richard Manser and Paul Lewis proudly represented Emerging T-Tech, engaging with a vibrant community and sharing insights on the future of intelligent automation. The event highlighted ground breaking advancements in agentic automation from leading organisations like Travis Perkins and NatWest, showcasing its transformative impact across industries.
Before diving into AI model development whether building or buying, leaders need a clear-eyed framework for decision-making. This post outlines the key strategic, technical, and operational questions every organisation should ask to avoid costly mistakes and ensure alignment with business outcomes.
Not every organisation has to choose between building or borrowing. This post explores how hybrid strategies combining pre-built models with custom fine-tuning, private hosting, or on-device optimisation, can deliver the best of both worlds.
Building your own AI model can be expensive, complex, and risky but there are scenarios where it pays off. This post looks at when developing a proprietary model offers genuine return on investment, and what conditions must be in place to justify the effort.
Building your own AI model may seem like a cost-saving move in the long term but the reality is often very different. This post explores the hidden and not-so-hidden costs of developing, training, and maintaining proprietary AI models, from staffing and compute to compliance and failures.
Choosing where and how to run your AI workloads can drastically affect your speed, cost, and scalability. This post breaks down the pros and cons of using hyperscale cloud providers, GPU-specific IaaS vendors like Cudo Compute, or running your own bare metal setup.
