Maritime AI has been built the wrong way for a decade — point tools bolted onto incompatible data, models trained on synthetic distributions that don’t survive contact with real ports, autonomy stacks evaluated in simulators their developers don’t trust. The result is a category that has consumed billions in capital and produced almost no real-world deployment. KEKOVA is built on a different bet: that the only way to deliver Physical AI for maritime infrastructure is to own the whole stack — from the sensor at the dock to the foundation model that generalizes across vessels and ports — and to run a data flywheel that compounds with every deployment. The four layers are tightly coupled by design. Each layer is a serious engineering problem in its own right. None is useful in isolation. Real-world sensor data trains world models. World models drive closed-loop simulation. Simulation expands the developer platform. The platform attracts the next generation of maritime autonomy — which produces the next generation of data. One company. One system. One compounding loop.