How to govern LLM token cost across a team
LLM cost is usage-based and mostly invisible until the invoice. One unbounded retry loop, one script left running, one team that quietly 10×'d its usage — and the number you see at month-end isn't the number you planned. Governance is how you turn that surprise into something you set, watch, and adjust. None of it requires a finance team; it requires a few controls in the right place.
Token governance is the practice of allocating, attributing, and capping the tokens a team spends on LLM calls — so cost stays a dial you control, not a bill you discover. (A token is the unit a model reads and bills in, roughly a word-piece.)
Why LLM cost gets away from teams
Three things make LLM spend slippery. It's usage-based — cost scales with behavior, not a fixed seat. It's opaque — a call's cost depends on prompt length, context, and the model, none of which are obvious at call time. And it's distributed — many people and services call the model, each adding to a bill no one owns. Put together, spend drifts upward quietly until something forces a look.
The six levers
Governance isn't one switch; it's a handful of controls working together. A good gateway puts them in one place:
Budgets per key and team
Issue a separate key per person, team, or project, each with its own budget. When a key hits its cap, it stops — a runaway script burns its own budget, not the whole company's.
Attribution
Tag every call to a who and a what. Without attribution, a bill is one big number; with it, you can see which team, feature, or experiment drives spend — and decide what's worth it.
Hard limits, not just alerts
Alerts tell you after the money's spent. Spend and rate limits stop the call before it runs. For anything automated, a hard ceiling is the difference between a bad day and a bad month.
Right-size the model
The biggest model isn't always the right one. Route each task to the smallest model that clears your quality bar, and reserve the heavy models for work that needs them. (Keep a capability probe so you know where the bar actually is.)
Cache what repeats
Identical or near-identical calls — the same system prompt, the same context — shouldn't be paid for twice. Caching at the access layer cuts the cost of repetition without changing your code.
See it in near-real-time
Usage and cost on one sheet, close to live — not reconstructed from a month-end invoice. You can only govern what you can see while there's still time to act.
A governance checklist
What good looks like:
- Every caller has its own key and budget — no shared, unbounded keys.
- Every call is attributed to a person, team, or project.
- Hard spend and rate limits guard anything automated.
- Tasks are matched to right-sized models, not defaulted to the largest.
- Repetition is cached, not re-billed.
- Usage and cost are visible in near-real-time, with a named owner.
Solunar Gateway
Solunar Gateway puts these controls in one place: per-key and per-team budgets, attribution on every call, spend and rate limits, caching at the access layer, and usage you can see — not a month-end surprise. The point isn't to spend less for its own sake; it's to make cost a number you set and defend. Access is invite-only.