The company thesis
Move the model to the operational data. Begin with renewable energy and use one well-scoped asset question to guide field validation.
RAIN / Company
Explore RAIN’s product direction, engineering ideas and progress toward a first renewable-energy field pilot.
Company background & explainers
01 / THE IDEA
RAIN brings model execution and learning closer to operational data. Explore the company thesis, the architecture behind a local learning loop and the questions a first pilot needs to answer. These are background resources, not announcements of completed field deployments.
Move the model to the operational data. Begin with renewable energy and use one well-scoped asset question to guide field validation.
Read telemetry, infer locally, evaluate candidate models and keep a record. The operator receives an advisory while control systems remain separate.
Move from a simulated battery plant to a scoped design-partner pilot. Learn whether the system can operate reliably and surface useful evidence on-site.
02 / IN PRACTICE
Define the scope, preserve the boundary, and make the outcome something a person can inspect.
Start with the local-first AI explainer for the relationship between signals, models and the facility boundary.
The evaluation guide explains why retraining and model promotion are separate decisions, and why rejected updates remain part of the record.
The pilot guide turns the product thesis into practical questions about access, signal quality, hardware and operator review.
03 / A FEW DETAILS
The press releases page describes the current project status. No formal press releases have been published on this site yet.
The Media & Press page includes a short description, naming guidance and the current project boundaries.
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.