Knowledge crosses system boundaries
Facilities, operations, IT, security, procurement, compliance, and sustainability each hold part of the process. The full workflow often exists only in handoffs and tacit knowledge.
Critical infrastructure
Process intelligence for AI data centers.
Capture the operating knowledge spread across facilities, operations, IT, security, procurement, compliance, and sustainability teams. Then compare opportunities, qualify root causes, model value, and decide what deserves investment.
The operating context
The gap between telemetry and investment decisions.
The IEA reports that global electricity demand from data centers is set to more than double by 2030, with AI the most important driver of that growth. Uptime Institute's 2024 survey reports operator practices and experiences across resiliency, sustainability, efficiency, staffing, cloud, and AI. Telemetry can show what infrastructure is doing; it does not, by itself, explain the cross-functional process that should change next.
Execution tools do not choose the work
DCIM, BMS, EMS, observability, ITSM, and automation platforms provide essential measurements or execution. They do not create a comparable investment case for every proposed operational change.
Ideas arrive with uneven evidence
A maintenance workflow and an energy-reporting workflow may use different language and metrics. Without structured intake, leaders cannot compare root cause, effort, risk, and value consistently.
How IntakeOS works
One comparable portfolio from many operating languages.
IntakeOS does not manage infrastructure. It manages discovery and qualification upstream of delivery, turning operating knowledge into ranked, evidence-backed work.
- VARA interviews cross-functional teams to capture current-state workflows, exceptions, dependencies, and tacit knowledge.
- Structured opportunities make unlike work comparable across utilization, cycle time, labor, rework, incidents, dependencies, and energy-related operating metrics.
- Deterministic qualification tests root cause and the appropriate improvement pattern before recommending technology.
- ROI models document inputs and assumptions; approved work routes into existing delivery tools for implementation and measurement.
Illustrative opportunity record
Cross-domain change coordination
InputsCycle time · rework
Next stepValidate root cause
A disciplined path to energy-efficient outcomes.
IntakeOS does not reduce PUE or WUE, control energy use, or optimize cooling. It helps teams discover and prioritize operational changes that existing engineering, control, and delivery systems can execute and measure.
Capacity and change workflows
Map approvals, dependencies, and facilities/IT handoffs. Compare cycle time, rework, utilization, and change-related incidents before deciding whether coordination should be redesigned or automated.
Illustrative operational use case
Maintenance and incident coordination
Capture how teams diagnose and resolve issues across observability, DCIM, BMS, and EMS outputs. Measure labor, elapsed time, repeat incidents, and avoidable handoffs; existing platforms remain responsible for telemetry and action.
Illustrative operational use case
Compliance evidence and energy reporting
Qualify reporting workflows using documented inputs such as collection time, data quality, rework, and reporting latency. IntakeOS structures the opportunity; source systems supply the operating and energy measurements.
Illustrative operational use case
Procurement and vendor workflows
Find bottlenecks in hardware procurement, approvals, spares, and contractor dispatch. Model value from lead time, labor, rework, downtime exposure, and utilization without claiming an outcome before implementation.
Illustrative operational use case
These are discovery scenarios, not measured IntakeOS results. Energy and thermal outcomes depend on engineering decisions, site conditions, implementation quality, and measurement in systems outside IntakeOS.
Clear boundaries
Decide what to improve. Let the stack execute.
IntakeOS is not DCIM, BMS, EMS, observability, process mining, workload scheduling, power or cooling control, or an automation-execution platform. It does not ingest live sensor telemetry or operate infrastructure.
It is an upstream process-intelligence and investment-decision layer: capture how work happens, qualify what should change, model why it matters, and hand approved work to the systems that build, run, and measure it.
Where IntakeOS fits
- 1. Discover and decideIntakeOS
- 2. Build and orchestrateITSM · workflow · automation
- 3. Observe and controlDCIM · BMS · EMS · observability
- 4. Operate infrastructurePower · cooling · compute
Primary references
IEA, Energy and AI (2025) — global analysis and projections for AI, data-center electricity demand, energy security, and emissions.
Uptime Institute, Global Data Center Survey 2024 — operator-reported practices and experiences across resiliency, sustainability, efficiency, staffing, cloud, and AI.
U.S. Department of Energy, Energy Efficiency in Data Centers — federal resources for constructing, operating, and maintaining energy-efficient data centers.
ASHRAE, Data Center Resources and Datacom Series — guidance on thermal conditions, cooling, energy, humidity, and data-processing environments.
Bring one operating process. Leave with a qualified decision.
See IntakeOS capture a cross-functional workflow, test the root cause, and build a documented value model before implementation begins.
Explore the platform