The Challenge
Industrial service providers do clever technical work to make their customers' operations more efficient — saving fuel, reducing emissions, extending equipment life. But the customer in many cases is a corporate sustainability office or a shipping company's investor relations team. They don't speak in compression ratios and exhaust gas temperatures; they speak in CO2 tonnes, ESG ratings and regulatory compliance. Today, translating engineering wins into customer-facing sustainability narratives is a slow, manual, expensive job. Can AI do it automatically and credibly?

Mission
Build a system that takes engineering-level efficiency improvements (fuel saved, emissions reduced, equipment life extended) and generates customer-facing narratives at multiple audiences: ESG report contribution, investor relations talking points, regulatory compliance evidence. Validate the narratives for accuracy with engineers and for resonance with sustainability professionals.

Why we suggest this
The translation layer between engineering metrics and customer-facing sustainability narratives is a manual cottage industry across the industrial sector. Decarbonisation services and ESG reporting are fast-growing revenue areas; the supporting communications infrastructure is not. Strong cross-portfolio applicability across any B2B sustainability services business. *Project will use AI-generated synthetic engineering improvement data and publicly available ESG reporting frameworks.*