Use casesAI inference spend
04

AI inference spend

Put a hard ceiling on model usage.

Route OpenAI-compatible model traffic through Featherlane AI to meter cost, warn before the limit, and stop new requests before provider spend crosses the cap.

Trigger

Every model request sent through a Featherlane AI gateway route.

What breaks

An agent loop, user, or team keeps consuming tokens while the provider dashboard only explains the bill after the fact.

Control point

Customer-owned model pricing, a visible usage dashboard, an 80% alert, and a hard cap enforced before the upstream call.
01Your app
02Featherlane AI gateway
03Budget decision
04Model provider

How it works

  1. 01
    Route

    Keep the client shape you already use

    Point the OpenAI-compatible base URL at Featherlane AI. The route binds the caller, agent, model, and provider without changing the chat payload.

  2. 02
    Meter

    Turn tokens into attributable spend

    Price and usage are recorded by model, principal, request, and budget window so the operator can see who consumed what.

  3. 03
    Warn

    Fire the 80% threshold once

    A budget alert warns the team while there is still room to investigate. The alert informs; it does not replace enforcement.

  4. 04
    Stop

    Reject the request before provider spend

    When the hard cap would be exceeded, Featherlane AI returns budget_exceeded and never forwards the request upstream.