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AI Model Economics Evidence & Implementation Kit

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AI Model Economics and Build-vs-Buy for Enterprise Architects · the model sourcing decision, made defensible · Evidence & Implementation Kit
Justify a model sourcing decision with numbers, without building the costing discipline from scratch.
Every control handed to you adopt-ready, from modelling total cost of ownership across the full stack through workload profiling, the self-host break-even, small models and distillation, multi-model routing and lock-in analysis to the cost attribution and drift governance a reviewer examines.
Ready in a weekend, not a quarter.

Here is the honest situation. Here is the honest situation. Reading a per-token rate is easy. Costing a model estate so a build-versus-buy call holds up in front of a CFO and an SRE is the hard part, and it is where most AI programs quietly overspend. A decision made on the headline price is wrong in both directions: standardizing on the top frontier model overpays on the majority of traffic a cheaper model would serve at the same quality, and self-hosting open weights to save money burns more than the API when utilization is low and the operations burden lands on a team that never budgeted for it. Doing this well means modelling total cost of ownership across tokens, inference infrastructure, fine-tuning, evaluation and operations, profiling a workload across latency, throughput and accuracy so the numbers reflect reality, and comparing a frontier API against self-hosted open weights at real utilization rather than peak. It means placing purpose-built small models and distillation where they earn their keep, routing across models so frontier prices are paid only on the residue that needs them, quantifying lock-in and keeping a costed exit, and reading the accuracy-cost frontier per task. And it means cost attribution, drift monitoring and renegotiation so the estate stays economical after the decision is signed. Where teams fall short is predictable: a headline-rate comparison, a self-host case built on peak utilization, one model standardized across forgiving and unforgiving tasks alike, and a model bill no one can attribute.

This Kit removes the guesswork. It is AI model economics written as adopt-ready controls you personalize in a weekend, with the evidence a reviewer examines.

What you get, the moment you buy

18
Controls, adopt-ready. Every control, written so you personalize and apply it.
18
Evidence-they-examine checklists. For each control, exactly what a reviewer examines, plus where teams fall short, so you close the gap first.
1
Control Matrix, pre-built. Every control in a working spreadsheet, ready to record status, owner and evidence location.
1
Gap & Readiness Assessment. Score each control and the workbook returns your readiness as a single percentage, and exactly what to fix next.

Grounded in enterprise architecture, platform engineering and FinOps practice applied to AI model sourcing. Editable Word and Excel files.

A model priced on its headline rate is a bill no one can explain
The per-token rate is the smallest and most misleading part of a model's cost. This Kit builds the full-stack TCO, workload-profiling, break-even, routing, lock-in and cost-governance controls that turn a model sourcing decision into an engineered one, with the evidence a review asks for.

What one control looks like

This is the opening control, where the costing discipline begins. All 18 are built to this depth.

AME-1 Model the full cost stack, not the headline rate TCO MODELLING AND THE COST STACK
Put this control in place

Require [your organization name] to build a total cost of ownership model for every candidate sourcing option that prices the full stack, direct consumption or compute, inference infrastructure and idle capacity, fine-tuning and adaptation, evaluation, and operations, and to compare options only as total against total rather than one vendor's headline rate against another's hardware floor.

Control note.

Two architectures that quote the same headline rate can differ by an order of magnitude once the stack is filled in, and that difference is exactly what a build-versus-buy decision turns on.

Evidence a reviewer examines
  • A TCO template covering all five cost layers for each sourcing option
  • Completed TCO comparisons expressed as total against total
  • The operations and idle-capacity lines populated with real numbers, not zero
Common finding they raise: Comparisons price only the direct consumption layer, which systematically flatters self-hosting by crediting the low compute floor while ignoring the infrastructure, evaluation and operations layers it moves onto your books.

Why this is not another template pack

  • The numbers are the point. A sourcing call you cannot defend with math is a guess waiting to be challenged. This tells you what an architecture or investment review examines and where teams fall short, for every control.
  • The economics specifics built in. Full-stack TCO, workload profiling across latency, throughput and accuracy, the self-host break-even at real utilization, small models and distillation, multi-model routing, lock-in and exit cost, and cost attribution and drift are written into the controls, not left generic.
  • Built on real practice, not one person's opinion, grounded in how model estates are actually costed and where the build-versus-buy decisions actually go wrong.
  • It compounds. This work shares its shape with enterprise architecture, platform engineering and FinOps, so it feeds your wider infrastructure and cost practice.

Who buys this

Enterprise architects, platform engineering leads and AI infrastructure managers who own the model sourcing decision and the cost line under it, and the finance and reliability partners who have to accept the build-versus-buy call. Whether this is your first model sourcing decision or a cost uplift on an estate already running, you save weeks and walk in with your TCO, profiling, sourcing, routing, lock-in and governance controls structured.

By the end of the weekend you will have
✓  An adopt-ready control for all 18 areas
✓  A completed control matrix
✓  The evidence a reviewer examines
✓  Every stage of the decision covered
✓  A readiness percentage and a fix list
✓  The highest-risk gaps closed

Common questions

Is it really editable? Yes. Word and Excel files you own and adapt. No portal, no subscription.

Does it cover the full sourcing decision? Yes. TCO modelling and the cost stack, workload profiling and requirements, model selection and sourcing, multi-model routing and reliability, lock-in and exit, and cost governance and operations each have their own controls with their own evidence.

Is this tied to one model vendor or cloud? No. The controls are principle-level, full-stack TCO, workload profiling, the self-host break-even, right-sizing and distillation, routing, lock-in analysis and cost governance, so they apply whatever models, providers or cloud you run.

What if it is not for me? A 30-day money-back guarantee.

Do not let your next model bill arrive as a number no one can explain.
Every control is fast to adopt with the Kit. It is instant, and it is guaranteed.
Add it to your cart and be ready this weekend.

Instant digital download · 30-day money-back guarantee · The Art of Service Pty Ltd, GPO Box 2673, Brisbane QLD 4001 · support@theartofservice.com

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