We have applied computer science and operations research in various capacities to develop solutions for energy and commodity trading, risk management, and commercial optimization. Our approach leverages advanced analytical techniques, primarily through open-source software and affordable computers, to pragmatically solve complex commercial problems. Some might refer to this as the "geek way" as it is relatively fast and cost-effective. However, we have frequently observed that traditional organizations struggle to implement this approach effectively. The primary barrier is often cultural. The pragmatic nature of the approach can highlight inefficiencies within the organization, revealing missed opportunities or expensive IT initiatives that failed to deliver as promised.

Rather than pursuing another costly digital transformation that rebuilds core systems, a smarter path forward uses Large Language Models as a flexible orchestration layer. This approach connects existing systems and workflows, integrating fragmented data into a structured, usable whole—without overhauling legacy architectures. It's a pragmatic solution that delivers immediate value while deferring risky, expensive system replacements. The real challenge isn't coding; it's business analysis—understanding organizational dynamics and designing agentic systems that turn that understanding into better, faster decisions.

Creating a collaborative, innovation-focused environment within the organization remains essential. Combined with intelligent data orchestration, this approach enables teams to analyze and act on unified data, accelerating insights and guiding a deliberate, step-by-step transformation that strengthens each core element over time. Check out these articles for a deeper exploration of our perspective: digital transformation and intelligent data orchestration.