AI tokenomics and gateway
One solution for understanding model costs, planning provisioned capacity and controlling the requests that create spend.
Process + responsibility
One cost model, with control in the request path
- 01
Connect
Read provider billing, token usage and provisioned capacity. Map deployments and keys to their owners.
Provider data
- 02
Understand
Compare effective cost per 1M tokens, including provisioned and reserved capacity, for the same time window.
Tokenomics
- 03
Route + control
Applications call the gateway. It selects permitted targets, handles configured fallback and enforces key policies.
AI gateway
- 04
Measure + tune
Review request costs, errors, latency and capacity utilization. Adjust policies and approve commitments with evidence.
Your AI + FinOps team
Gateway policies control routed requests. Capacity purchases and renewals require named approval.
Choose your starting point
| Your objective | Start with | Access needed |
|---|---|---|
| Understand AI spend without changing applications | Connect AI providers, then tokenomics methodology | Read access to provider billing, inventory and usage telemetry |
| Attribute and control new model requests | Gateway quickstart | Provider invocation credentials, a route and a scoped gateway key |
| Review provisioned throughput and commitments | Capacity sizing | Per-minute utilization history and reservation inventory |
How the pieces fit
- Provider billing supplies pay-as-you-go, provisioned capacity and reservation charges. Token telemetry supplies the usage denominator.
- Tokenomics allocates those costs to deployments, models and owners, and calculates effective cost per 1M tokens.
- The optional gateway routes application requests through configured targets and records team, tokens, cost, status and latency.
- Budgets, reports and capacity recommendations use this evidence. Gateway policies act on requests that pass through the gateway.
Two different permissions
Validate the first integration
- Select one provider, one deployment and a closed billing window. Compare imported charges with that provider's export.
- Check input, output and cached token counts. Review unmatched meters before comparing models.
- If using the gateway, send a test request with a dedicated key and confirm its route, owner and request metadata.
- Test fallback and budget limits in a non-production application before increasing traffic. Validate output compatibility when switching models.
Data handling
Gateway requests pass through KubeOn to the configured model provider. Prompt and response bodies are not stored by default; route logging changes that behavior. Review redaction, region restrictions and the model provider's own data handling before sending sensitive content. See routes, keys and limits and the trust center.