Paragon Energy AI

Renewable operators run hundreds of millions of dollars of assets across fleets of equipment from a dozen manufacturers, in the field, on connectivity that comes and goes. Most analytics live in the cloud, observe from a distance, and go blind the moment the link drops. Paragon inverts that. The intelligence runs at the edge, on the device, where the decision has to be made.

Each agent watches for the failure the operator would have felt, acts on it locally within the authority it has earned, logs the warranty claim, and explains itself: “I throttled this inverter because its temperature curve matched the last three failures — here is the data.” That single sentence — local action plus a plain-language reason — is what turns a skeptical operator into a believer, and it is the whole design.

I built Paragon from a blank page — the corporate structure, the customer relationships, the capital strategy, and the code itself. I architected and personally shipped the autonomous edge agent that lives on every device in the fleet. Most CEOs in regulated infrastructure cannot ship the product. That changes the economics of building it — and it means the person accountable for the business is the same person accountable for whether the customer's experience actually improves.

Because that is the point. Paragon is not an AI project with a customer-experience benefit bolted on. It is the customer's experience — an operator who finally trusts the software watching their plant — delivered by pointing AI, capital, and product at one outcome. It is the thesis I write about, running in the field.