A connected platform collects operational telemetry from distributed solar micro-inverters and provides fleet-wide visibility into performance, device health and faults.
Every project follows the same Ryvasys Split — AI drafts the mechanical work, a named engineer reviews and owns every decision that touches safety, cost, or a regulatory limit.
Additional detail on architecture, stack and implementation specifics for this engagement.
Each micro-inverter's telemetry is captured through a protocol-specific firmware integration and relayed through a gateway layer into a cloud ingestion pipeline, which feeds a web dashboard giving fleet-wide visibility into performance and faults across distributed installations.
Telemetry (power output, operating parameters, fault codes) is collected from inverters via their native communication protocol, normalized at the gateway, and streamed to the cloud for aggregation, storage and analytics that support both real-time monitoring and historical performance analysis.
Interpreting and normalizing telemetry across a fleet of distributed, sometimes-heterogeneous inverter installations — including handling intermittent connectivity from field sites and defining fault semantics that are actionable rather than noisy — was the core engineering problem, alongside building a data architecture that scales as the fleet grows.
A gateway-mediated architecture was used rather than direct device-to-cloud connections because field installations often have limited or shared connectivity infrastructure, and a gateway layer gives a single reliable uplink point per site while insulating the protocol-specific integration work from the cloud pipeline.
