Trusted by maintenance teams
across manufacturing, energy, and utilities
From CNC floors to offshore compressors, DiagAI helps industrial operators detect failures earlier, diagnose root causes faster, and eliminate unplanned downtime.
Companies running DiagAI in production
Case studies
Real deployments, real results.
Apex Automotive
Manufacturing43% reduction in unplanned downtime across 12 CNC lines
Apex Automotive deployed DiagAI across their stamping and CNC machining floor. Within 90 days, the anomaly detection pipeline had flagged 17 early-stage spindle faults that would have caused unplanned stoppages. Total avoided downtime cost in the first year: $1.4M.
“DiagAI's RCA reports give our maintenance team a clear starting point every time. We used to spend hours tracing faults — now it's minutes.”
— Head of Reliability, Apex Automotive
NovaDrill
Oil & GasZero undetected compressor failures in 18 months of production
NovaDrill integrated DiagAI's API with their SCADA system to monitor 9 compressor signals in real time. The knowledge graph's SWRL rules for corrosion and seal degradation patterns proved especially accurate in their offshore environment, producing zero false-negative alerts across 18 months.
“Offshore compressor failures are expensive and dangerous. DiagAI gives us confidence that nothing is slipping through the cracks.”
— VP Operations, NovaDrill
GridForce Energy
UtilitiesMulti-domain failure detection across wind turbines and substations
GridForce deployed DiagAI for both wind turbine drivetrain monitoring and substation transformer health. The cross-domain knowledge graph transfer meant that failure patterns learned on turbine gearboxes also improved transformer insulation anomaly detection — without retraining.
“The cross-domain learning is genuinely impressive. We didn't expect turbine fault patterns to improve our transformer anomaly detection, but they did.”
— Chief Engineer, GridForce Energy
What our customers say
“The multi-agent reasoning is what sets DiagAI apart. It doesn't just say something is broken — it tells you why, what to do, and what will happen if you wait.”
“We were sceptical about an AI system understanding our specific failure modes. The knowledge graph customisation changed that completely.”
“Integration with our existing CMMS took less than a day using the REST API. The docs are genuinely good.”
“Sub-2-second RCA on a live sensor stream — I didn't think that was possible before we saw the demo.”
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