Fixed-fee implementation · 48 hours
Not a dashboard. Not a report. We wire hard spend controls directly into your agent stack, prove they trigger with a controlled spend-burst test you watch, and hand you the keys. If the test fails, you owe nothing.
According to the operator's published disclosure, one Codex prompt spawned 826 agents and burned $78,000 with no alerts and no caps. We wrote the teardown. The lesson is blunt: watching a dashboard does not stop a runaway. The controls have to live in the run path, at agent speed.
The asymmetry: your local token counters and your vendor's billing ledger are two different instruments, and nobody reconciles them in real time. Every startup running agents in production is one bad prompt away from a five-figure invoice.
The test is agreed before we start: a controlled spend burst must terminate on budget breach, the alert must reach your channel, and the audit log must show the full sequence. If any of that fails, you owe nothing and we remove everything we installed.
No retainer. No per-seat pricing. No percentage of savings. One number, agreed before we start, paid when the system proves itself in front of you.
If you run agents in two production workloads, we scope both at signature: €5,000 for the first implementation, €5,000 for the second. The first ships in 48 hours; the second on a separately agreed window. Each milestone is invoiced only after its own signed acceptance test. One signature, one decision date, no phased maybe-later.
Why this exists: a single workload is €5,000 of protection. Two workloads is the full commitment — and the only structure where the economics make sense for both sides.
| What teams pay today | Typical cost |
|---|---|
| CloudZero AI Signals at $100K AWS spend | ~$1,500 / month, forever |
| nOps | $149 / month + ~20% of savings |
| One unmonitored agent runaway | $6,500 – $78,000, once |
| 48-hour guardrail implementation, pay on accepted test | €5,000, one time |
That is the entire ask. 48 hours, then we hand you the keys. Your security team reviews the exact permission scopes on the kickoff call before anything is granted.
Supported stacks. We implement at the layer you control: an LLM proxy (LiteLLM, Portkey, OpenRouter), a framework wrapper (LangChain, CrewAI, OpenAI Agents SDK, custom), or cloud-native metering (AWS Bedrock / SageMaker with CloudWatch + Lambda enforcement). If your agents run somewhere we cannot meter and terminate, we tell you on the scoping call and you owe nothing.
Rollback. Every component we install is removed on request, in one documented procedure, with no residual permissions. The 48-hour window includes a rollback drill: we remove the guardrails and confirm your stack is byte-identical to before we started.
The acceptance test, agreed in writing before we start.
You sign the test result. That signature triggers the invoice. If any check fails, we fix it inside the 48 hours or you owe nothing.
Startups running AI agents against real workloads: coding agents, support agents, research agents, anything with tool access and a billing meter. If your agents only run in a sandbox with no spend, you do not need this yet.
I am Indiko jabua, a solo founder. I built ScaleToZero after watching teams burn five figures on cloud spend nobody flagged. This is not a SaaS signup and not an agency black box: you work with me directly, I install the guardrails in your stack, and I hand you the keys.
15 minutes. We confirm your stack is compatible and book the 48-hour window. If it is not a fit, we tell you on the call and you owe nothing.
Request scoping call