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AI cost and token usage dashboard

See Exactly What AI
Costs You. Drive Adoption. Reward ROI.

Tetrate Agent Router Enterprise gives you one AI cost dashboard to attribute token usage per person, application, or team across your full agent network.

AI cost dashboard showing total cost, requests, tokens, and cost over time

The Adoption Mandate

"We need AI usage metrics to show the board the investment is working."

Leaders made headcount and budget decisions on the assumption that AI makes teams more productive. If teams aren't using AI, then they aren't more productive. See who is using AI and push the ones that aren't.

The ROI Mandate

"We need to show that AI spend is tied to real business outcomes."

Is AI spend producing something? Knowing who is spending tokens isn't enough. Finding out why teams spend tokens needs data. For the gateway-level approach to showback and chargeback:

Your AI bill is an AI gateway problem

Segment AI token usage by any combination of person, team, application, and agent network

A provider bill reports spend by provider. Agent Router Enterprise attributes every token to the caller, and because agents call other agents, attribution follows the full chain.

By person

Every request carries the authenticated identity of the developer or service account that made it. See which engineers use AI and how much, down to the individual. Identify power users and people who haven't made a single request this month.

By team

Roll individual usage up to the team level for budget reporting, showback, and chargeback. See which teams are on track for adoption targets and which teams are heading toward a budget overrun. Set per-team token limits that stop requests before the bill arrives.

By application

Attribute spend to the specific application or workflow that consumed it. When three teams use the same underlying agent platform, you can see which application drove which spend, and which team's API key made each call. Useful for product ROI analysis and deprecation decisions.

Any combination

Slice attribution data by any combination of these dimensions. "Show me all spend by the risk team on the compliance-check application, attributed to individual engineers." Every request carries all four dimensions, so you filter from the dashboard with no custom reporting.

Enterprise AI cost management dashboard metrics for leadership

Adoption

  • % of developers with active token usage this month
  • Teams below adoption target, with the count and token gap
  • Week-over-week usage trend by team
  • Model diversity: are teams using capable models or defaulting to the cheapest?

Spend

  • Total spend by team, attributed to the caller behind each API key
  • Budget adherence % by team, flagging teams approaching their budgets
  • Cost per workflow or application, rolled up from each model call
  • Requests blocked inline at a token limit, with the spend each block prevented

ROI signal

  • Cost per agent workflow, tying token spend to a unit of business output. Smart routing tiers models by cost per finished task, not price per token.
  • Provider comparison: the same model's cost across providers
  • Wasteful patterns: retry loops, oversized prompts, and unused agent chains
  • Cost efficiency trend: are teams using tokens more efficiently over time?

Frequently asked questions about AI cost dashboards

An AI cost dashboard shows how much an organization spends on AI model requests and which people, teams, or applications drove that spend. It handles LLM cost tracking by reading the token count and cost of each request, then grouping them for showback, chargeback, or budget reporting. Agent Router Enterprise builds this view from traffic passing through its gateways, where every request carries the identity of the caller.

Tracking token usage by team requires every model request to carry the identity of the person or service that made it. A gateway in the request path can record that identity with the token count, then roll individual usage up to teams. Agent Router Enterprise attributes each token to a person, team, agent, or project. It also exports cost and token metrics to your own observability tools.

An AI adoption dashboard tracks who is using approved AI models, how often, and how usage changes over time. Common metrics on a team AI usage dashboard are the share of developers with active usage, teams below an adoption target, and week-over-week usage by team. Agent Router Enterprise shows these next to spend metrics, so a platform team can report adoption and cost in the same review.

Yes, when one system records traffic to every provider, such as a gateway in the request path. A provider's own usage page covers only the traffic sent to that provider. Agent Router Enterprise routes requests to multiple providers through one endpoint, so token usage and cost for every provider appear in the same dashboard. Smart routing then chooses the model for each request inside policy.

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