Uncovering Hidden Infrastructure Losses With AI Insights
AI Infrastructure Health: Hidden Losses Uncovered Card summary: AI insights revealed underused solar, premature generator activation, and battery misconfiguration. Galooli’s X-Ray tool fixed the root cause remotely, no site visits, no hardware changes
~$600K
Annual savings
-25%
Generator runtime
+120%
Battery utilization
+10%
Solar utilization
Overview
Off-grid hybrid solar sites promise lower fuel costs and a smaller environmental footprint, but only if solar, battery, and generator assets are actually working together as designed. Without real-time visibility into how each asset is performing against its expected output, inefficiencies can hide in plain sight for months, quietly adding up across a large site network.
How Galooli Solved It
From a hidden efficiency gap to a fully remote fix, no site visit required, in four steps.
Hidden Losses Building Up
Solar underused, generators engaging early, batteries misconfigured, across 1,500+ sites with no visibility.
AI Compares Real vs. Expected
Galooli's AI benchmarks each site's live data against its expected solar performance to surface the pattern.
X-Ray Tool Fixes It Remotely
Misconfigured rectifier settings corrected over-the-air, no technician dispatched, no hardware touched.
Measurable Results
~$600K saved annually, with generator runtime down and battery/solar utilization sharply up.
Generator Runtime
25%
After Galooli
Before Galooli (100%)
Battery Utilization Efficiency
120%
Before Galooli
More than double, after Galooli
The Challenge
A telecom operator managing more than 1,500 off-grid hybrid solar sites had no way to tell whether those sites were performing as intended. Diesel generators were engaging earlier in the day than they should have, batteries weren’t being used to their full capacity, and available solar generation wasn’t being fully captured, all invisible without a way to compare actual performance against expected performance at each site.
Galooli's Solution
Galooli’s AI compared each site’s real-time data against its expected solar performance, immediately surfacing the pattern behind the losses: underused solar, premature generator activation, and misconfigured battery settings. Rather than dispatching a technician to investigate and fix each site individually, Galooli’s X-Ray tool remotely corrected the misconfigured rectifier settings causing the problem, improving how batteries were used and reducing diesel reliance, all without a single site visit or hardware change.
Outcomes
Generator runtime dropped 25%, worth roughly $15,000 a month in fuel and maintenance savings. Battery utilization efficiency rose 120% as higher discharge rates let batteries carry more of each site’s energy load. Solar utilization increased 10% as the corrected configuration made better use of renewable capacity already installed on site. Altogether, total site energy costs fell 25%, adding up to roughly $600,000 in annual savings, achieved entirely remotely.
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