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Tokenomics

Per-agent token metering with budget caps, attribution, and real-time cost transparency. Know exactly what your AI fleet costs and why.

1

What is Tokenomics?

Tokenomics is Agent.ceo's built-in cost management layer. Every LLM call made by every agent in your fleet is metered, attributed, and budget-checked in real time. You get full visibility into what your AI workforce costs — down to the individual tool call.

Per-Agent Metering

Every token consumed by an agent is tracked individually. See exactly which agent used how many tokens, on what task, and when.

Budget Caps

Set per-agent or org-wide token budgets. Agents pause automatically when they approach their limit — no surprise bills.

Attribution Model

Tokens are attributed to the agent, task, and org that triggered them. Drill down from org-level spend to individual tool calls.

Org-Level Dashboards

See aggregated token usage across your fleet. Identify which agents and tasks consume the most resources at a glance.

Real-Time Tracking

Token counts update in real time as agents work. No waiting for end-of-month invoices — you see spend as it happens.

Configurable Alerts

Set threshold alerts at 50%, 80%, and 100% of budget. Get notified before limits are hit so you can adjust proactively.

2

How It Works

Token metering is transparent to agents — they make LLM calls as normal, and the platform handles tracking, attribution, and budget enforcement automatically.

1

Agent makes an LLM call

When an agent calls Claude, GPT, or any supported model, the gateway intercepts the request and records the prompt and completion token counts.

2

Tokens are attributed

Each call is tagged with the agent ID, task ID, org ID, and model used. This enables drill-down from org spend to individual tool invocations.

3

Budget is checked

Before each call, the agent's remaining budget is checked. If the estimated cost would exceed the cap, the call is blocked and the agent is notified.

4

Dashboard updates

Token usage appears on the org dashboard in real time. Admins can see per-agent breakdowns, daily trends, and cost projections.

Attribution Model
Organization (monthly budget)
├── Agent: CEO         ─── 12,400 tokens/day  ── budget: 500k/mo
│   ├── task-abc123    ─── 3,200 tokens
│   └── task-def456    ─── 9,200 tokens
├── Agent: CTO         ─── 28,600 tokens/day  ── budget: 1M/mo
│   ├── task-ghi789    ─── 15,400 tokens
│   └── task-jkl012    ─── 13,200 tokens
└── Agent: Fullstack   ─── 45,100 tokens/day  ── budget: 2M/mo
    ├── task-mno345    ─── 22,800 tokens
    └── task-pqr678    ─── 22,300 tokens
3

Getting Started

Set up token budgets for your organization in three steps.

1

Set a budget

Go to your org settings and set a monthly token budget. You can set org-wide limits or per-agent caps for fine-grained control.

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2

Deploy agents

Deploy your agent fleet as normal. Token metering is automatic — no configuration needed on the agent side.

3

Monitor usage

Check the tokenomics dashboard to see real-time usage, per-agent breakdowns, and cost trends. Adjust budgets as your fleet scales.

Ready to control your AI costs?

Set budgets, track usage, and get full cost transparency across your agent fleet.