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Unit 02 · Financing
Stop renting
depreciating hardware at someone else's margin.
Renting GPU capacity is priced to cover the provider's hardware, their facility, their operations and their profit. If your workload is predictable — and by the time you're in production it usually is — you're paying a premium for flexibility you no longer use.
Financing turns that operating expense into an owned asset without the capital call that ownership normally implies.
The Constraint
The Three Ways To Fund
AI Hardware All Have
a Catch.
Capital purchase, cloud consumption and leasing are genuinely different instruments — not three prices for the same thing. They differ on who holds the asset, where the cost lands on your statements, and what you're left with at the end of the term.
Capital purchase competes with everything else
Buying outright is the cheapest total cost of capital and the hardest budget to get approved. It also consumes cash that, in an early-stage company, is usually worth more deployed into headcount or runway.
01
Cloud rental never stops
Consumption pricing is genuinely right for spiky, unpredictable work. For a steady production workload it compounds indefinitely and leaves you owning nothing — while the provider depreciates the asset.
02
Funding hardware with equity is the worst trade
Raising a round to pay for equipment that loses value on a fixed schedule means selling permanent ownership of your company to cover a depreciating line item. Debt exists precisely for this.
03How we do it
From a Cloud
Bill to an Owned
Cluster.
The work is mostly arithmetic and structuring. We do the modeling openly, including the cases where the answer is that you shouldn't finance at all.
Baseline the real cost of your current model
We build the comparison off your actual consumption — instance mix, utilization, committed-use discounts, egress, storage and the hours you're paying for but not using. A great many cloud-versus-own comparisons fail because the cloud side is estimated from list price rather than an invoice.
OUTPUT CURRENT-STATE TCO FROM REAL INVOICES
Model ownership against it
The same workload is costed as owned infrastructure: hardware, fabric, storage, colocation power, support and refresh assumptions, over three and five years. The output is a breakeven utilization — the point above which owning wins and below which it doesn't.
OUTPUT BREAKEVEN ANALYSIS AND TCO MODEL
Select the structure
Capital lease, fair-market-value lease, or a term loan against the equipment are all viable and behave differently on your balance sheet and your tax position. Which one fits depends on how long you intend to run the hardware and how you want the obligation to present.
OUTPUT RECOMMENDED STRUCTURE WITH RATIONALE
Assemble the credit package
We prepare the submission — financials, contracted revenue where it exists, deployment plan and asset schedule — and take it to our OEM finance partners and institutional lenders rather than having you approach them cold and sequentially.
OUTPUT CREDIT PACKAGE AND LENDER SHORTLIST
Structure the draws around the build
AI deployments ramp; a flat payment schedule from day one penalises you for hardware still in transit. Payments are aligned to delivery and commissioning milestones so cost tracks capability.
OUTPUT EXECUTED DOCUMENTS WITH DRAW SCHEDULE
Plan the end of term before you sign it
Buyout, extension, refresh or return should be a decision you priced at the start. We model residual positions up front so end-of-term isn't a surprise negotiation from a weak position.
OUTPUT END-OF-TERM OPTIONS SCHEDULE
What's included
What The Financing
Unit Covers.
TCO Modeling.
Cloud-versus-own breakeven built from your actual invoices.
Structure Advisory.
Capital lease, FMV lease and loan compared for your position.
Finance Partner Panel.
OEM captive finance and institutional lenders approached in parallel.
Credit Packaging.
Submission prepared and syndicated on your behalf.
Milestone Draws.
Payment schedules aligned to delivery and commissioning.
Buyout Options.
Dollar-buyout and percentage-buyout structures where they fit.
Sale-Leaseback.
Release capital from GPUs you already own and redeploy it.
Refresh Planning.
Mid-term upgrade paths that don't require re-tranching the facility.
Full-Stack Coverage.
Fabric, storage, power and cooling financed alongside the accelerators.
Residual Modeling.
End-of-term positions priced before signature, not after.
Structures Compared
Four Funding Models,
Side By Side.
There is no universally correct row here. The right structure follows from how long you'll run the hardware, how your tax position works, and how much balance-sheet flexibility you need.
Buy outright
Capital lease
FMV lease
Cloud rental
Questions
Before You
Commit
It depends entirely on utilization, and we'd rather show you the arithmetic than assert a number. Ownership wins decisively on sustained, predictable load because you stop paying for idle capacity and for someone else's margin. Below a certain utilization threshold, rental genuinely wins — and if your workload sits there, the model will show it.
Under our structured facilities, we build in mid-term technology refresh paths where older nodes can be redeployed or traded toward next-generation accelerators without resetting your entire financing agreement.
No. While bundling hardware financing and high-density colocation offers operational advantages and a single invoice, we can finance hardware destined for your existing on-premises data center or another third-party facility.
Yes. We underwrite based on institutional backing, cash runway, balance sheet health, and recurring enterprise contracts. Early-stage venture-backed AI companies regularly qualify when sponsored by established funds.
Typically, the conversation involves both your engineering leads (who define compute requirements, duty cycles, and growth) and your finance team/CFO (who evaluate runway impact, Capex vs Opex preferences, and tax positioning).
Bring us a cloud invoice.
We'll show
you the
breakeven.
No structure recommendation until the model says ownership is the right call for your utilization.
Talk to an engineer
The Rest of the Stack
Six Units. One
Assembled Stack.
GPU Procurement
GPU Financing
GPU Colocation
IB & RoCE Networking
High Performance Storage
GPU Management
Note on figures. Savings ranges reflect comparisons against public cloud list pricing for sustained workloads and vary substantially with utilization, committed-use discounts and term length. Illustrative only, not a quote. Enzu is not a tax, legal or investment advisor — balance sheet and tax treatment, including depreciation and expensing elections, should be confirmed with your own advisors.