There are two costs. Build it, and run it.
To build what this site runs on, a comparable team without AI is modeled at $2.7M loaded (a $1.4M-$3.9M band), recompiled nightly from the delivered scope: code, docs, and shipped products. Against the operator hours behind it, that is about $5,068/hr of equivalent build per effective hour. One operator did it instead. To run it, monthly, is the comparison below. Both are comparators, not bills anyone paid us.
Same output. Three bills.
Loaded cost of the headcount to run this the old way. You get a team and a paper trail. Slow, and priced like it.
Point a model at it and pay the compute. Fast and nearly free. No leader, no record, no way to say who approved what.
The runtime, plus a human on the gate and a signed, hash-chained record. The speed of the model with an account you can defend.
The middle column is where most of the market is standing right now. It is the cheapest way to get output and the most expensive way to get caught.
What these numbers are not.
A comparison is only proof if it is honest about its own edges.
Receipts, not revenue
These are the costs of real runs, not proof of a paying book of business.
Prototype, not certified
A running prototype under real controls, not an accredited or certified system.
Comparators, not quotes
The traditional figure is a loaded-cost comparator for the work, not a bill anyone paid us.
Four instruments we run on ourselves.
A live meter for whether the AI sounds like its operator, a failing grade we published and held, a contaminated test we voided and disclosed, and a fire drill whose rules are locked before any score exists.
The proof runs live in the War Room.
The comparison above is settled in public, in real time, on the proof surface.