One AI bill with no breakdown is not a cost model. Cost Management attributes LLM, token, and compute spend to the app and the team that caused it, so the fastest-growing line in your budget finally has owners.
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AI spend by app and team
Per app, per team, before the invoice lands
Attributed to the app and the team that caused it
AI spend is the fastest-growing line item in most IT budgets and the least attributable: one invoice covering every app, team, and experiment, with no way to split it. Because every app already runs on Helix, the runtime is the natural place to meter what each one consumes and attribute it to the app and the team that caused it. Cost stops being a monthly autopsy and becomes something you can act on.
AI spend is the fastest-growing line item in most IT budgets and the least attributable. Finance asks who spent it, and nobody can answer.
One invoice covers every app, team, and experiment. Splitting it is manual archaeology at best.
A single misbehaving agent can burn a quarter's budget over a weekend, and nothing surfaces it until the invoice.
Without per-app history there is no basis for predicting next quarter, so budgeting becomes guesswork.
When spend is unpredictable, the safe answer to a new AI project is no. Uncertainty becomes a brake on adoption.
See what each app costs to run rather than one aggregate number for the org, so the AI line item has something behind it..
Roll cost up to the workgroup, so budget conversations happen with the people actually spending..
Set an expected envelope and watch consumption against it, rather than discovering the number at the end of the month..
Halt an app consuming far beyond its budget before the invoice lands, instead of reading about it afterwards..
This is about the AI, token, and compute cost of the apps your teams deploy, not general cloud FinOps. A narrower problem, solved properly.
Available today by design. The AI that writes the code runs on your own Claude subscription, so build-time cost is paid to the provider directly and never marked up here.
Because every app already runs on Helix, the runtime is the natural place to meter what each one consumes. Spend is attributed where it happens rather than reconciled from a provider invoice weeks later.
Because every app runs on Helix, spend can be attributed at the point it happens rather than reconciled from a provider invoice weeks later.
A billing dashboard tells you what you already spent. Attributing spend to a named app and owner is what makes it possible to act before the money is gone.
Everyone else sells the building. Helix prices the running, and the AI that writes your code stays on your own subscription.
When AI costs jump, sort by spend and land on the exact app and owner behind it rather than opening an investigation.
Marketing gets a budget for the apps it ships, and its consumption is visible against that number rather than pooled into one org total.
An agent stuck in a retry loop is stopped against its limit instead of burning a quarter's budget over a weekend.
Per-app history gives budgeting a basis, so the AI line stops being a guess with a safety margin bolted on.
When an app's cost sits next to its usage, retiring the ones that are not worth running becomes an easy call.
No. The AI that writes your code runs on your own Claude subscription, so build-time spend is paid to the provider directly and never lands on the Helix meter. What is metered here is what your apps consume when they run.
No. It is scoped to the AI, token, and compute spend of the apps your teams deploy through Helix. Cloud FinOps is a different problem with tools that already solve it.
A billing dashboard reports what you already spent. Attributing spend to a named app and owner at the runtime is what makes it possible to act before the money is gone.
Yes. Early access is where this gets tuned, so tell us what you need from AI cost and it feeds into the design.
See what your AI spend looks like when every app and team carries its own number.
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