Eleven AI tools. Name one number they moved.
AI spend is the easiest cost in the company to see and the hardest to attribute. Most tools meter usage, so cost scales with activity while value stays anecdotal. You are paying more the busier your teams get, with no way to tell busy from productive.
Then renewal season arrives, and the honest answer to "which of these is working" is a shrug with a slide deck behind it.
The question is not what AI costs. It is what it returns, and whether you could ever tell.
Value measured per workflow, in your numbers.
Boxcar prices around governed workflows in production and measures what each one returns while it runs. You pay model providers directly; we never mark up usage or meter your activity, because the platform should not get more expensive the more you run through it. Every workflow either proves it deserves to double or shows you exactly why to cut it.
And the spend stops evaporating. Every governed workflow leaves the company owning its own reasoning: decisions, alternatives, evidence, inheritable by the next person and the next agent. An asset that compounds, not a burn that renews.
One governed rollout returned $500K in week one.
A multi-region retail operator consolidated duplicated tooling onto one governed substrate and recovered $500K in licensing in the first week, with local autonomy intact and the gains tracked in their own numbers, not asserted in a readout.
Right now, nothing: while we are in early access, the product is free to existing and approved pilot customers. The core is Apache 2 open source, and the Enterprise Plane adds sophisticated access controls, a zero technical debt engine, support, and IP indemnity. The positions above hold either way: no markup on your model usage, and no metering. Want in on early access? That is a conversation we would enjoy.
Put a number on one workflow
Five weeks. One workflow. Measured value, and you keep every artifact whether or not you continue.