Know exactly what soiling is costing you
Disaggregate your losses. Optimize your cleaning schedule. Stop guessing.
Solar Portfolio Analytics
800MW • Multi-Region • Real-Time Monitoring
Today's Power Output
3Active Alerts
Inverter Status (96 units)
Environmental Conditions
The Problem We Solve
Soiling losses are hidden in your data
You know your plant is underperforming, but you can't tell how much is soiling versus equipment degradation, inverter clipping, or environmental factors. Without clear attribution, cleaning decisions become guesswork — and you're either overcleaning (wasting budget) or undercleaning (leaving revenue on the table).
Faults announce themselves too late
By the time an inverter trips or a string goes offline, you've already lost production. Traditional threshold alerts catch failures, not the gradual degradation that precedes them. You need visibility into what's failing before it fails.
No portfolio-level financial visibility
You have SCADA data per plant but no unified view of how your portfolio performs against financial projections. Revenue leakage from soiling, downtime, and degradation goes unquantified — making it impossible to prioritize where O&M spend delivers the most return.
What We Do
We build ML systems that disaggregate your losses — separating soiling from faults from environmental factors — and quantify the financial impact across your portfolio, so you can act on what actually matters.
What I Help With
Portfolio-level anomaly detection
Solar inverters, BESS cells, wind turbines
Digital-twin architectures
For EMS & SCADA environments
Data pipelines for utility-scale monitoring
Solar, BESS, wind — cloud & edge
ML model strategy
What to build, what not to build
Technical due diligence
For monitoring platforms & integrations
Multi-channel alerts & automated reporting
SMS, Email, Teams, Google Chat, WhatsApp — with scheduled KPI reports
Remote control & emergency response
Emergency shutdown & isolation on critical events via SCADA integration
AI-powered O&M assistant
LLM agent that interprets alerts and recommends corrective actions
About NuraVolt
NuraVolt combines physics-based modeling with machine learning to turn your existing monitoring data into predictive intelligence. We layer on top of any SCADA or inverter platform — detecting faults days before impact, optimizing cleaning schedules, and forecasting battery health. Easy integration in 2-3 weeks, cloud or on-premise.
Latest Insights
Expert insights on solar PV monitoring, battery storage analytics, and energy intelligence for UAE/GCC operations.
October 2025
The Cost of Poor Irradiation Data Quality in PV Monitoring
Discover how poor irradiance data quality costs solar operators millions in missed performance issues, false alarms, and suboptimal O&M decisions.
October 2025
Common BESS Faults Where ML/AI Adds Value Over Classic Monitoring
Discover how machine learning catches battery storage system faults that traditional BMS monitoring misses, from thermal runaway to capacity fade prediction.
Frequently Asked Questions
Get answers to the most common questions about our platform
Ready to Start Your Pilot Program?
Our international team is ready to show you exactly how much you're losing and how we can recover it. Get your custom ROI calculation and start the pilot program.
Free Technical Resources
Whitepapers and checklists to improve performance monitoring and reduce O&M costs
Browse All ResourcesLet's Discuss Your Monitoring Challenges
Whether you need architecture guidance, a full implementation, or help building internal capabilities — I work across the spectrum.