For CFOs

Know where your AI budget is heading and what it’s paying for.

Track AI spending against budgets, connect costs to project work, and maximize your AI investment.

Tokenize overview dashboard showing spend by provider, token usage, cost per user, and team adoption

AI Budgets

Plan for AI spending.

Review recorded spend and monthly forecasts across teams, see which teams are approaching their budgets, and plan token budgets and allocations by team and project.

Learn about budgets →

AI ROI

Assess what your investment supports.

Connect token costs to outcomes and deliverables across engineering and non-technical teams. Work with team leaders to assess the value of AI outputs.

Learn about AI ROI →

AI Cost Savings

Put your budget toward useful work.

Review inefficient AI setups and correct wasteful token sessions without costly changes to team workflows.

Learn about cost savings →

Frequently asked questions

See all FAQs
How is this different from the usage dashboard my AI vendor already gives me?

Vendor dashboards show you that vendor, and only the teams on it. Tokenize shows every AI tool side by side, across every team, with one definition of cost. It also connects spend to the work it produced, which vendor billing pages do not do.

Does it tell me whether the spend was worth it?

It connects spend to output, so you can see what a piece of work cost and what it produced. You still make the judgment call. We give you the evidence to make it with.

What happens when a team hits its budget?

You get alerted, with the forecast that led there. Budgets are there to make spend visible early, not to cut people off mid-task.

Can I see usage by team?

Yes. That is the default view. Usage rolls up by person, team, and department, so you can see where the work and the money go and who to talk to about it.

Will this slow my teams down?

No. The controls run in the background, and Tokenize emphasizes visibility over approval steps. People do not have to ask permission each time they use an AI tool.

Can we try it before rolling it out to everyone?

Yes, and we recommend it. Start with a few teams, look at what comes back, then decide how wide to go.

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