Engineering judgement first. AI where it earns its place.

Industrial companies have collected data for decades. Historians hold years of pressures, flows and temperatures; shared drives hold years of tickets, invoices and reports. Very little of it gets used beyond the shift it was recorded on.

Modern machine learning and language models change what is practical. A model can learn what normal looks like for a compressor, or read a stack of field tickets, at a cost that makes sense for a single site. What is still scarce is people who understand both the models and the plant.

That is the gap we work in. We pick problems where the value is clear, build the smallest thing that proves it, and leave you owning the result.