The next constraint is not intelligence, it is the energy cost of running it. We deploy custom AI models inside energy companies that ingest SCADA data, work orders, and grid topology, operational data no public model has seen, grounded in physics-informed neural networks and differentiable grid simulators. This creates a flywheel: more operator data → better process understanding → more efficient operations → cheaper energy → cheaper AI → more deployment → more data. https://www.youtube.com/watch?v=0uDH6pMn5OE AI compute doubles every 2.2 years. Data center demand grows from 415 to 945 TWh by 2030. Without near-zero energy cost, AI remains limited by human infrastructure. We are the layer that runs AI at zero energy cost. Energy is a $10 trillion market. The infrastructure layer doesn't exist yet. We are building it.