Cost & Budget Controls
The runtime that secures and governs every AI interaction also meters what each one costs. Spend is measured on the governed path as it happens and attributed to the people, teams, and agents who created it. Budgets enforce inline, before the model call. The invoice stops being the first time you find out.
Cost & Budget Controls
Metered on the path
Usage measured per request as it happens, on the same governed path where policy enforces, across providers.
Caps that hold
Budgets enforce inline, before the model call.
Attribution that sticks
Every request carries user, team, department, cost center, model, and provider.
Agents metered too
Agent workloads carry the same attribution and meet the same caps; a runaway loop hits its budget at enforcement time, not on the invoice.
Finance-ready reporting
Dashboards and exportable reports for chargeback, showback, finance reviews, and board updates.
Optimization signals
Recommendations for model substitution, caching, and over-provisioned agents, drawn from the traffic that ran.
AI spend grows with no visibility and no budget controls
Provider invoices arrive weeks after the tokens burned, aggregated past the point where finance can attribute them, and the tools that could have stopped a runaway workload were never on the path to see it. Month-end reporting explains the bill; it cannot hold a budget.
Enforcement, not accounting
Spend is governed where security is governed: every metered interaction crosses the same four functions, and a cap is a decision made at enforcement time.
Live spend
Every interaction metered as it happens on the governed path, attributed at request level, across providers
Budgets that hold
Caps enforce at the same point policy does: inline, before the model call; at the cap, your policy decides what happens next
Real allocation
Spend attributed to user, team, department, cost center, model, and agent from runtime context, carried on the request itself
One console
Spend and adoption sit beside threat activity, fed by the same runtime decisions
Spend, live in the same console
The console shows total spend, API calls, cache savings, and budget utilization, live, beside the security posture the same decisions feed.
One policy surface: the console that enforces your security policy meters your spend. Both views are fed by the same runtime decisions.
Metering, caps, and attribution
How does the runtime's metering relate to provider invoices?
The runtime meters usage as it happens on the governed path: per request, with the user, team, model, and provider attached at enforcement time. Provider invoices remain the bill; they arrive later and aggregate. Runtime metering exists for control and attribution at the moment of use. It enforces caps, allocates spend to the teams that created it, and catches a runaway workload while it is still running.
What happens when a budget hits its cap?
Whatever your policy says. At budget enforcement the runtime supports allow (record the overage), alert (notify owners and keep going), hold for human review (further calls wait for an approval), or block (calls stop until the budget is raised or resets). Caps enforce inline, before the model call, so a cap is a decision made at enforcement time rather than a number discovered at month end.
How granular is attribution? Can we run chargeback?
Request-level. Every governed interaction carries user, team, department, cost center, model, and provider, and agent workloads are attributed the same way. Dashboards and exportable reports support chargeback, showback, finance reviews, and board updates without spreadsheet reconstruction.
Related solutions
Secure every AI interaction
Talk to Sales about your 30-day free trial
- Detect
- Redact
- Hold
- Block