Evidence first
Model results are evaluated in time order. Synthetic demonstrations and real observations stay clearly identified.
We believe understanding solar performance should feel clear, connected, and grounded in evidence.
A solar plant tells a story through its data. We help you see how the pieces connect — and where to look next.
Production, equipment, and data quality, together.
Physical references and intelligent models add context.
Turn investigation into an informed maintenance plan.
Model results are evaluated in time order. Synthetic demonstrations and real observations stay clearly identified.
Production, equipment, weather, and maintenance tell a fuller story when considered together.
Alerts support investigation. Technician feedback and confirmed incidents help build a stronger evidence base.
SolarGain currently runs as a development and demonstration platform with historical analysis, trained ML/DL models, and simulated integrations.
Live equipment connections, external notification delivery, and production deployment require the relevant service credentials and infrastructure. Predictive maintenance needs sufficient confirmed field incidents before its accuracy can be assessed.
Explore the details →