routers pick a model per call. fluxcompute optimizes the whole agent trajectory

fluxcompute sits between your agent's code and the model providers. You set limits on cost, latency, and quality. At every step, fluxcompute decides how to get the best result from the whole run while staying inside them, using up to 65% less compute.

How it works

01

you define the limits

Set the budget, latency, and quality bounds for the whole run, not for each call.

02

fluxcompute decides at every step

Before each step, fluxcompute looks at what's left of your budget, latency, and quality targets and chooses how to run it.

03

finish inside your limits

Every run ends within the bounds you set, with a full record of each decision and why it was made.

Who it's for

For teams whose agents are the product, and whose inference bill grows with every run.

Your agents take many steps.

Long, multi-call runs where cost and latency compound.

Your inference bill is hard to predict.

Spend grows with trajectory length, and you can't cap it without hurting results.

You've hand-tuned it yourself.

Hard-coded models per task, swapped in cheaper ones, and still worry about quality.