Condition intelligence for the rotating equipment that keeps data centers running.
SibylCor helps data center owners and operators understand developing conditions across critical power and cooling equipment earlier—so they can reduce downtime risk, plan maintenance with greater confidence, and protect asset availability.
A physical investment cycle—not just a software trend.
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57%
of surveyed operators said their most recent major outage cost more than $100,000. One in five exceeded $1 million.
Source: Uptime Institute, Annual Outage Analysis 2026 (2025 survey) (opens in a new tab)
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200 GW
global data-center capacity could reach by 2030, requiring up to $3 trillion of investment.
Source: JLL, 2026 Global Data Center Outlook (opens in a new tab)
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~90 GW
of behind-the-meter generation announced across 59 U.S. data centers. About 2 GW was operating as of mid-2026.
Source: Cleanview, Behind-the-Meter Data Centers (2026) (opens in a new tab)
Every new facility adds assets; every operating facility creates a continuing reliability obligation.
From business-as-usual intervals to condition-informed decisions.
Detection creates warning; diagnosis and prognosis create time; planning converts that time into avoided disruption.
Old operating default
- Calendar and OEM intervals
- Threshold alarms and manual triage
- Emergency work after a trip
- Maintenance as a cost center
Emerging reliability discipline
- Scheduled service combined with continuously assessed condition and duty cycles
- The underlying failure mode diagnosed and the evidence quantified
- Degradation forecast; parts, technicians and service windows reserved earlier
- Reliability, productive capacity, risk and maintenance expenditure optimized together
Time to power
- 1–3 years typical development time for a data center
- 5–15 years to plan, permit and complete new grid infrastructure
Critical power and cooling equipment
Turbine, engine, generator, pump and chiller uptime, using the sensors, data acquisition, historians, controls and maintenance systems already in place. No proprietary hardware.
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Power Generation
Gas turbines, reciprocating gas engines and diesel standby generator sets, on site and behind the meter
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Cooling Systems
Centrifugal chillers, cooling-tower drives, and the pumps and fans in coolant distribution units and computer-room air handlers
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Support Equipment
Pumps, compressors and motors across fuel, water and supporting plant
Built to diagnose the equipment—not just detect the signal.
SibylCor aims to find developing faults before conventional alarms, identify the affected failure mode with supporting evidence, anticipate how degradation may progress and recommend when to intervene.
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Observed
A relationship drifts that the model cannot explain away, with no single reading in alarm.
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Reconciled
Physics-based equipment models calculate parameters that cannot be measured directly and reconcile them with operating data.
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Ranked
Competing failure hypotheses are tested against live evidence, each with a failure mode, component and confidence.
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Recommended
Work window, people, parts and work orders, through SibylCor’s workflows or the site’s CMMS, EAM and ERP systems.
What this changes
- Reserve parts earlyThe most consequential shortage can be a hot-gas-path part, rotor component, blade or qualified repair slot.
- Align service specialistsA developing bearing, blade, combustor or compressor fault is identified with sufficient lead time.
- Schedule with flexibilityWork is planned while the plant still has operating flexibility.
The earlier the developing failure is understood, the more manageable the exposure becomes.
Uptime economics are changing the maintenance mindset.
Protecting productive capacity is becoming a strategic reliability decision, not just an annual maintenance expense.
The risk is not just the price of a machine. It is lost output, scarce repair capacity and delays in restoring redundancy.
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Reduce downtime risk
Developing faults in on-site power and cooling are diagnosed before they become outages.
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Plan with greater confidence
Every recommendation carries its failure mode, supporting evidence and confidence.
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Protect asset availability
A turbine can represent tens or hundreds of millions of dollars in equipment value; a backup generator can cost more than $1 million.
SibylCor is designed to compute the Total Cost of Risk for each monitored asset: process unavailability, degraded efficiency, emergency procurement and missed operating windows.
Equipment values: Wood Mackenzie end-2027 gas-turbine price forecast (April 2026) applied to representative turbine classes; listed asking price for a 3 MW diesel generator set (2025).
“Outages overall have slowed down, and overall, digital infrastructure is remarkably resilient. But further resiliency gains are becoming harder to achieve.”
Independent industry context. Quotation does not imply endorsement of SibylCor.
Who we’d like to talk with
Hyperscale and colocation operators
Turbine, engine, generator, pump and chiller uptime behind every committed megawatt.
Behind-the-meter power developers
When generation moves on site, its availability, fuel, controls, service and reserves become the operator’s risk.
Engineering and commissioning firms
The right sensor package specified at design, so critical equipment is ready for failure-mode diagnosis from day one.
We’d welcome a conversation about the equipment and maintenance challenges that matter most to your facilities.
Or email info@SibylCor.com
Start with one critical asset class
One critical asset class, one narrow engagement—starting where the consequence of failure is already understood, with a low-risk path to validate SibylCor.