AI usage is costing more than you allocated
Organizations usually discover their AI costs after the fact: via an invoice, a quarterly report, an audit, or a nightmarish headline.
Metering is Swept's cost control offering, a real-time layer that tracks token consumption and spend across any LLM within your organization. We enforce your preset per-user budget (which can be broken down by employee, by task, by department, etc.) by metering spend halting usage when approaching those budgetary limits. Think of it like a circuit breaker.
The circuit breaker doesn't shut down all AI tools within your organization, just the use-case(s) that are approaching budget limits. You'll receive an alert and your team's approved human decision-maker chooses how to proceed. You stay in control. Swept documents everything, keeping your AI budget a known (and provable, audit-ready) quantity.
What We Do
Customize your metering
You set the thresholds. Per-user budgets, per-department limits, alert triggers, circuit breaker rules…all of it is defined by your organization and editable by approved users. Swept enforces your rules, not a generic policy.
Supervise & actively monitor
Our metering monitors spend across every model and every employee in real time. When usage approaches a defined threshold, alerts route to your team with context: what triggered, what the limit was, and what the relevant history looks like. Your team decides how to respond while we document the decision.
Track and document everything for governance, compliance & audit readiness
We log every cost event, alert, threshold breach, and resolution. Spend history is maintained continuously and feeds directly into your governance reporting. Your record will always remain current so that you're prepared whenever a review, audit, or board conversation requires it.
Provide cost-efficiency through workflow fit
There's a second cost problem that metering alone doesn't solve: AI deployed broadly, on tasks where it doesn't produce value. Swept approaches this issue beginning with your workflow. We baseline what your team actually does and identify where AI produces measurable value. The result is a cost profile that reflects deliberate decisions rather than unchecked adoption. What gets monitored, and at what limits, reflects how your organization actually operates.
Offer easy toggling between LLMs based on task
Not every task needs the most expensive model. When usage patterns or budgets call for it, you will be able to move a user, team, or workflow to a right-sized model with a single click. Using the best model only where it matters most provides measurable savings.
Support any LLM
Swept is AI-agnostic; we monitor cost across every model in your environment: Claude, GPT, Gemini, etc. You're not locked into a single vendor's reporting dashboard. The complete picture lives in one place regardless of how many LLM models your organization uses.
Provide hands-on support with a named engineer
Swept assigns an engineer who knows your systems, your team, and your goals. Initial configuration, integration, and rollout support are part of the engagement. This includes guidance on how to right-size your models and tools, which ensures that your Swept support remains cost-conscious.
What You Get
- Real-time token tracking/cost metering with budget controls at however granular a level you require: per-employee, per-team, per-task, and per-department, for example
- Circuit breakers for cost overruns which are reviewed and (if chosen, overridden) by an approved human decision-maker within your team
- One-click model switching to right-size an employee, task, team, or workflow if a simpler/cheaper LLM is sufficient for the use-case.
- Configurable alerts before your thresholds are reached
- A full audit trail of spend, flags/alerts, thresholds, and resolutions
- Cost data integrated into governance and compliance reporting
- Workflow-grounded implementation: deploying AI tools only when the ROI warrants it