Use case · Control AI Cost

Stop reconciling AI spend by invoice.

Provider APIs and model routing in one place. See what every team and budget actually spends, down to each agent on its own API key, and stop it when the budget runs out, not when the bill arrives.

Start 30-day free trial Book a demo

budgets · live spendMETERING

Budgets reporting: accountable spend and usage by budget

The problem

You can't control what you can't measure.

AI spend is scattered across personal subscriptions, enterprise seats, API keys, and model providers, with no single view of where the money goes.

Scattered spend

Personal Claude and ChatGPT plans get expensed on top of company seats. Usage across the two never lands in one place.

No cost attribution

Tokens bill to a single org-wide key. There's no way to tie spend back to the team, product, or agent that drove it.

Runaway agents

Autonomous agents loop, retry, and burn tokens with no budget, no alert, and no ceiling, while you get left with the bill.

Why it matters now

AI is becoming the new cloud bill, only it's climbing the curve faster.

AI moved into production across every team at once. Spend compounds month over month while the tooling to govern it lags behind.

Employees bring their own subscriptions alongside company seats. Finance sees invoices, never the usage that drives them.

The same visibility and chargeback finance demanded of cloud is now expected of AI, but spend is split across every provider.

The solution

One control plane for all AI spend.

Actualyze sits in the path of every AI call to meter usage, attribute cost, and enforce budgets across every provider and every team.

Meter every source in one ledger

Every call through the platform is metered in one normalized ledger; token counts captured on every request, attributed to the team and budget that made it, across every provider.

Provider spend across OpenAI, Anthropic, Azure OpenAI, and Bedrock
Dollar cost layered on provider pricing
Token-level metering in the request path

Attribute spend down to the team

Internal allocations break every dollar down by team, budget, and cost center, and by agent when each agent runs on its own API key. Attribution coverage tracks how complete that mapping is so chargeback is provable rather than estimated.

Per-team and cost-center allocation
Attribution coverage across every budget
Chargeback readiness with cost-center codes

Enforce budgets before the bill

Create budgets mapped to your business, each with an optional monthly limit: an alert before it and a hard stop at it. Month-to-date spend and a projected month-end sit on every budget, and spend that maps to no budget still shows, in dollars. A runaway workload stops before it becomes a runaway invoice.

Hard monthly limits on budgets, with an alert before each
Month-to-date spend and a projected month-end
A monthly limit on each agent's API key, so one loop can't drain the shared budget

The platform, mapped to cost

Token spend, managed from every angle.

It isn't a bolt-on. The same control plane that governs, secures, and routes every call is what makes spend visible and predictable.

Govern

Budgets & access, set once

Define budgets and model access per team in one place, with an alert before every limit. Budget hierarchies keep every child budget inside its parent's limit.

Explore Govern

Secure

Every dollar is auditable

Each metered call is logged with the team, model, and policy behind it; spend you can prove, not estimate.

Explore Secure

Operate

Live spend in view

Observability shows requests, tokens, and spend by provider as they happen, filtered by team, budget, model, or API key.

Explore Operate

Optimize

Cheaper per request

Routing and failover send each call to the most efficient model that still meets the bar: lower cost, same result.

Explore Optimize

Integrate

Spend across every provider

Meter cost across every provider, SDK, and connector through one path; no per-vendor reconciliation.

Explore Integrate

FAQ

Questions about controlling AI cost.

Does this track personal AI subscriptions, or only company API usage?

Actualyze meters the calls that route through the platform: provider APIs and your model router, attributed to teams and budgets in real time.

Everything bills to one org-wide key. How do you attribute cost?

Every request through Actualyze carries the API key that made it, and each key is bound to one team and one budget. Give each agent its own key and you see agent spend too. Even when the provider only sees a single key, spend maps back to the team and budget that actually drove it, which is what makes chargeback possible.

What happens when an agent loops and burns tokens?

Set a hard monthly limit on any budget, with an alert threshold before it. At the limit, Actualyze refuses the next call before any model is contacted. Give each agent its own API key with a monthly limit, and one runaway loop stops without draining the shared budget or turning into a runaway invoice.

Providers report dollars differently. How do you keep cost comparable?

Token counts are captured at the call level, so usage stays comparable across every provider. Dollar cost is layered on from each provider's rates to give you one normalized ledger instead of a stack of incompatible invoices.

Can we charge AI spend back to teams or cost centers?

Yes. Every call carries its team and budget, and budgets carry cost-center codes your accounting system recognizes, so spend maps to the lines finance already reconciles against.

Do we have to route every call through Actualyze to see cost?

To see cost mapped to your teams, budgets, and cost centers, yes. Calls in the request path are metered in real time, across every provider behind the endpoint.

Make AI spend something you can see, attribute, and cap.

Get one view of every dollar across every team and budget, plus the controls to keep it predictable.

Start 30-day free trial Book a demo