01
Wire one app safely
Start in observe mode, keep production continuity intact, and validate live requests without forcing traffic through a new path on day one.
Live AI usage operating layer
AI spend that starts from the request, not the invoice.
Tokenometer measures real AI traffic, attributes it to named app identities, reconciles provider history when it exists, and turns token consumption into something teams can actually govern.
Truth source
Live traffic first
Provider history is useful reconciliation, not the only accounting story.
Identity layer
Named integrations
Apps become attributable objects with ownership, health, environment, and rollout state.
Governance
Same layer
Budgets, approvals, allocations, and chargeback ride on the exact usage events.
Inside the product
Product proof, not a mockup
Demo + live modes
Tokenometer already ships the operator surfaces that matter: rollout, verification, reporting, reconciliation, and governance.
Gateway
Wire and validate one app safely
Ledger
Verify the raw usage event
Reports
Read spend with reconciliation context
Why this exists
Provider billing surfaces are part of the picture, not the whole picture.
Tokenometer exists because the operational truth usually lives closer to the request than to the monthly statement.
Provider dashboards tell you what you spent after the fact.
Tokenometer measures the request where it happened and keeps the raw usage event attributable to the app behind it.
Historical APIs are inconsistent and often require elevated keys.
Tokenometer treats provider history as reconciliation input, not the only source of truth.
Finance, ops, and product look at different surfaces.
Ledger, reports, allocations, and exports all sit on top of the same usage layer.
Operator loop
A calmer way to wire AI products into accountability.
02
See the raw event
Every request can carry provider, model, integration, project, team, workflow, request ID, metering path, and token totals.
03
Reconcile reality
Pull provider-side history when it exists and compare it against live metering instead of pretending the providers all expose the same truth.
04
Govern spend
Move from observation into approvals, budgets, wallet controls, allocations, and chargeback on top of the same usage layer.
Product proof
A control plane with working operator surfaces already in place.
Tokenometer is already built around real surfaces for rollout, verification, reporting, reconciliation, and governance. This is the product, not a teaser.
Dashboard
Watch live usage, provider distribution, project attribution, and reporting freshness without losing the operational detail underneath the topline numbers.
Gateway
Choose observe, fallback, or enforce. Generate snippets, validate integrations, and inspect the request path without losing app identity.
Ledger
Inspect the raw event stream with filters, live totals, integration labels, and metering-path visibility.
Spend
Read daily, weekly, and monthly usage with reconciliation context instead of a disconnected cost chart.
Who it is for
For teams treating AI usage as infrastructure, not as an afterthought.
AI product teams
Teams shipping multiple provider-backed apps and needing clearer attribution than provider dashboards usually give them.
Platform operators
People responsible for rollout safety, continuity, provider choice, model drift, and integration visibility across environments.
Finance and governance
Stakeholders who need a spend story they can trust, with reconciliation, ownership, exportability, and policy controls.
Try it properly