Rexolution provides a cloud‑native software platform that aggregates real‑time telemetry from solar panels, wind turbines, weather stations and IoT sensors into a unified analytics hub. It applies machine‑learning models to forecast generation, detect performance anomalies, and issue predictive‑maintenance alerts, while delivering customizable dashboards and API integration with SCADA, ERP and ticketing systems. The solution enables utility‑scale renewable operators to increase capacity factor, reduce unplanned outages and extend equipment life.
Funding
Funding not disclosed
Founders
Product
Problem
Utility-scale solar and wind operators often lack a unified view of real‑time asset performance and predictive insights, causing missed energy‑yield opportunities and unplanned equipment downtime. Existing monitoring tools are fragmented, requiring manual data aggregation and offering limited forecasting accuracy. Consequently, asset managers struggle to optimize operations and maximize profitability.
Solution
Rexolution delivers a cloud‑native software platform that consolidates live sensor streams from solar panels and wind turbines into a single analytics hub. The system applies machine‑learning models to forecast generation, detect performance anomalies, and schedule preventive maintenance before failures occur. Users can visualize key performance indicators on customizable dashboards and receive automated alerts when metrics deviate from expected ranges. By integrating with standard SCADA and ERP systems via open APIs, Rexolution enables seamless data flow and supports automated control actions to fine‑tune turbine yaw or panel tilt for optimal output. The platform’s predictive analytics reduce unplanned outages, improve capacity factor, and extend equipment life, thereby increasing overall asset profitability.
Target Audience
The primary customers are utility‑scale solar and wind farm operators, asset‑management firms, and O&M service providers seeking data‑driven optimization of renewable energy assets.
Features
- Real‑time ingestion of telemetry from inverters, turbines, weather stations, and IoT sensors via MQTT, OPC‑UA, and REST endpoints
- Machine‑learning‑driven yield forecasting and degradation modeling with confidence intervals
- Predictive maintenance engine that flags component wear, inverter failures, and blade‑pitch anomalies before they cause downtime
- Automated alerting and workflow integration with ticketing systems (e.g., ServiceNow, Jira)
- Drag‑and‑drop dashboard builder with KPI widgets, heat maps, and time‑series visualizations
- Bi‑directional API layer for SCADA, ERP, and third‑party market‑data integration (REST, GraphQL, FHIR‑compatible)
- Cloud‑scale architecture with role‑based access control, end‑to‑end encryption, and ISO‑27001 compliance