The problem we are working on
Equipment detail can disappear in aggregate reporting. Site conditions vary, while a cloud-dependent workflow introduces connectivity and data-sharing constraints.
RAIN / Company
RAIN is building on-site AI hardware and software, beginning with the operational questions of renewable energy facilities.
Pre-seed · preparing for a first field pilot
01 / THE IDEA
RAIN is building DOM, an edge AI hardware and software system for facilities that need local inference, local learning and control over their raw telemetry. Renewable energy is the starting point. A simulated battery-storage plant provides the current foundation for the learning loop.
Equipment detail can disappear in aggregate reporting. Site conditions vary, while a cloud-dependent workflow introduces connectivity and data-sharing constraints.
RAIN Node provides the planned local compute layer. The runtime captures telemetry, runs models, evaluates updates and records history for operator review.
The system observes and advises. Raw telemetry stays local, and plant control remains separate. Operators decide what happens next.
02 / IN PRACTICE
Define the scope, preserve the boundary, and make the outcome something a person can inspect.
Telemetry capture, local storage, inference, retraining, promotion, rollback and audit components run against the battery-storage simulator.
Scope a design-partner pilot to test the hardware, signal quality, alert usefulness and sustained operation under site conditions.
Use field evidence to shape onboarding, support and commercial terms. Extend to additional assets as their adapters and use cases are validated.
03 / A FEW DETAILS
RAIN is the company name used on this website. DOM is the edge AI hardware and software system described in the project overview and the homepage hero.
No field deployment is claimed. The current implementation runs against a simulated battery-storage plant, and the next milestone is a scoped first pilot.
BUILD WITH RAIN
RAIN is preparing for its first field pilot. Start by defining the environment, the data boundary, and what success should look like.