Your AI agents are spending like a department
Govern them like one
Per token prices keep falling, and your agent bill keeps climbing. Sandton AI is building the system that shows where agent spend is going and holds it inside limits you set, without freezing the experimentation that keeps you competitive.
The cost doesn't show up
where you're looking
Cheaper tokens don't shrink the bill; they multiply agent volume. A single always on agent can quietly run a six figure rate rereading the same context thousands of times. The spend builds inside engineering budgets, then arrives all at once as margin compression in the financials.
of FinOps teams now manage AI spend, up from 31% two years ago. (State of FinOps 2026)
of companies plan agent deployments in the next two years; only 21% have a governance model. (MIT Tech Review / Deloitte, 2026)
annual run rate a single always-on agent can reach before anyone approves the spend.
"By the time finance sees it, it's a variance to defend. A blanket freeze just trades one mistake for another. Spend has to be governed as it happens, not explained after."
The thinking behind it
Your AI spend isn't one number
You'd never manage payroll as a single figure. Agent spend is the same: govern it by the outcome each agent drives.
Stop the bleed, not the experiments
A blanket freeze kills the experimentation that keeps you ahead. Cap what's wasteful, per agent, and leave the rest alone.
Govern where it's fragile
Runaway loops, rereads, agents that never sleep. Guardrails belong where systems break, not in a quarterly review.
Independent by design
No models sold, no compute resold, no cut of tokens. The system exists to lower your cost per outcome, nothing else.
Built by people who have run the spend and built the agents
Sandton AI is building governance infrastructure for AI agents in production: a system that stops runaway loops before they compound and puts a cost-per-outcome number in front of a CFO. It draws on years inside enterprise transformations, seeing where automation breaks and finance loses visibility.
Who this is built for
Engineering & platform leaders
Running agents in production and needing the overrun caught before it reaches the board.
Finance leaders
Needing agent spend to show up as a managed, predictable line, not a surprise or a panic freeze.
Private Equity backed & scaling teams
Under pressure to prove AI value without letting the burn rate spiral.
Want to know more about
what we're building?
Tell us a bit about your team and your agent stack, and we'll be in touch with more details.