The blind spot
AI compute economics are not GPU hours × price
What every invoice shows — and the six rows it hides.
These six rows are tenant economics. Most stacks stop at the seam between compute telemetry and the physical bill.
what a CFO rarely gets a defensible answer for
“If we add 5 MW of AI load, which tenants pay for it — and where does the margin go?”
Today that question is answered with a spreadsheet, a rule of thumb, and a pricing model built on assumptions nobody has measured.
The chain
Seven stages from observation to control
Metering
01 · What was consumed?
Attribution
02 · Who consumed it?
Billing
03 · What do we charge?
Cost allocation
04 · Who carries the overhead?
Capacity planning
05 · Where is the ceiling?
Optimization
06 · Where is the waste?
Control
07 · What can we safely adjust?
energy-aware billing→power pass-through→cooling allocation→premium power tiers→workload-aware pricing
In the pilot
Meter, attribute, allocateReconcile against your metersReport cost, confidence and gaps
Expansion path
Energy-aware invoicingPower pass-through and premium tiersCapacity planning against thermal headroom
Not claimed today
Autonomous billingClosed-loop controlReplacing your DCIM or scheduler
The meter
How it works
M-01collector
Lightweight agent observes GPU, CPU, RAM, power, network and workload IDs — no monitoring stack replaced.
M-02power
Integrates with PDUs, energy meters, UPS, BMS, PLCs and Modbus devices into one normalized model.
M-03cooling
Compute creates heat, heat creates cooling demand, cooling consumes facility energy — the chain is modeled end to end.
M-04allocation
Defensible cost methodology from simple GPU hours to compute + electricity + cooling + facility overhead, exposed not hidden.
M-05output
Recommendation-first: optimization starts as advice; control requires explicit authorization and comes later.
cooling is a differentiatorcompute → heat → cooling → cost
illustrative split — your real ratio is measured in the pilot
█ power cost█ cooling demand█ facility & rack overhead
The ledger of record
What the operator gets
three answers · one neutral layer
who consumed what · what it cost · what to do next
01
A commercial answer the industry lacks: who consumed what, what did it cost, and what should happen next.
02
New revenue streams — energy-aware billing, power pass-through, cooling allocation, premium power tiers, workload-aware pricing.
03
Capacity planning that answers: which racks are constrained, which tenants are growing fastest, what happens if we add 5 MW of AI load?
04
An economic flywheel — more telemetry → better attribution → better billing → better pricing → better utilization → more demand.
Get your true-cost readout
One cluster. One tenant. One rack. We show you what it consumed, what it cost, and which part of that number is measured versus allocated.
Book a pilot scoping call →Tenants
Who it's for
AI cloud & GPU clusters
Meter actual consumption per tenantEnergy-aware billingIdentify underutilized GPUs
Colocation & managed GPU
Power pass-throughCooling allocationPremium power tiers
High-density compute
Rack and thermal constraintsCapacity planningWorkload-aware pricing
Enterprise operators
Defensible cost reportsPUE and facility economicsLongitudinal cost intelligence
Methodology
Every number shows its working
We label each line of cost as measured, allocated or not claimed, so you always know how much of a number is a sensor reading and how much is a method.
measured
GPU / CPU / RAM / network per workloadPower at PDU, rack, UPS or facility meterWorkload duration and queue timeYour own tariff and invoice figures
allocated
Cooling apportioned by rack heat contributionFacility energy split across tenantsRack, network and storage overheadPUE, depreciation and shared capacity
not claimed
Accredited financial measurementAutonomous billing or re-billingClosed-loop facility controlA confidence score on unattributed usage
The pilot
One cluster, one defensible cost model
A read-only engagement on a single cluster, rack row or infrastructure zone, reconciled against your existing meters and current allocation rules. Three to four weeks, including at least fourteen days of representative load.
You provide
Read-only access to compute telemetry and to at least one layer of power measurementYour current allocation rules, tariff structure and contract constraintsA named operations or finance owner to sign off on the output
We provide
A normalized model joining compute telemetry, power, cooling and facility overheadA reconciliation against your invoices and meters, with every discrepancy listedAn allocation methodology written in plain language, with its assumptions exposedA cost model for one commercial decision you name at kickoff
This pilot is for you if
You are running GPU capacity for more than one tenant and cannot defend the allocationYou have meters worth trusting — PDU, rack, UPS or facility — and someone who knows what they coverA specific commercial decision is waiting on a better number: a rate increase, a power pass-through, a new pricing tier, an expansion case
how the pilot runs
Week 1
Source inventory, access and a written methodology agreed before any number is produced.
Weeks 2–3
Collection and normalization across the zone. No writes, no control actions.
Week 4
Reconciliation, gap report and the cost model for your decision.
You leave with
Tenant-level cost for the zone, with the share that is measured versus allocated stated per lineA reconciliation report listing what we could not explainA written recommendation on the commercial decision you named — and the conditions under which it holdsA stated confidence range for every cost line, with its sources listed
What we do not do in a pilot
We do not control infrastructure, move workloads, or touch power distribution in the pilotWe do not generate customer invoices or change your contractual termsWe do not replace your DCIM, scheduler or billing platformWe do not claim the accuracy of an accredited financial measurement
How it is priced
Fixed scope for the pilot. Metered infrastructure units after.
The pilot is a fixed fee with a defined scope and a defined zone. Production pricing scales with the infrastructure you choose to have measured, not with seats.
Pilot
Fixed fee. One zone, fixed duration, reconciliation and one decision model.
Platform
Monthly fee per monitored cluster or infrastructure zone, covering collection, normalization and reporting.
Modules
Optional. Energy-aware billing, power pass-through, capacity planning, optimization.
Data
Your telemetry stays yours. We do not resell tenant data, and the pilot can end with your export.
You keep your customer contracts, your tariffs and your pricing decisions. We make the underlying economics defensible.
Questions operators ask first
Readiness, boundaries, and what we won't claim
What can you actually measure, versus estimate?
Compute and power at the level your instrumentation reaches are measured. Cooling and facility overhead are allocated under a rule you approve. Anything inferred is labelled as inferred, with a confidence score, and a pilot will show you exactly which lines fall in each category before you rely on them.
Is this accurate enough to bill customers from?
The pilot is designed to get you to that decision, not to skip it. We recommend invoicing only on lines that reconcile against your meters, and we will tell you which lines those are — including when the honest answer is that your current metering cannot support it yet.
Do you replace our DCIM or billing platform?
No. DCIM owns facility operation, FinOps owns cloud spend, and orchestration owns scheduling. GridMind joins those layers to produce tenant economics. We would rather integrate with what you have than ask you to replace it.
How do you allocate cooling?
Cooling is apportioned by rack-level heat contribution under a rule you choose and we document. We show the result under alternatives so you can see how much of the answer is the rule and how much is the data.
What if our workloads are not cleanly labelled by tenant?
Then that is the first finding, not a blocker. The pilot will quantify how much usage is attributable versus unattributed — which is usually the most valuable output, because it is the number your current allocation is quietly guessing.
Will GridMind automate billing or control our infrastructure?
Not in the pilot, and not by default. Control requires explicit operator authorization and is a later stage. We produce recommendations and evidence first; anything that moves power or money stays behind a human decision until you decide otherwise.
What you can't meter,
you can't price
Start with one cluster and one decision you cannot answer today. We will tell you whether the data supports it — and if it does not, we will say so.