Commercials · 7 min read · Aug 12, 2026
Three cost lines, and what moves them.
Almost nobody publishes this, which is why every buyer assumes the worst. The monthly running cost of a bespoke AI operating system breaks into three lines. Here is what sits in each, and — more useful — which ones grow when you add outlets and which ones don't.
Why the number is usually hidden
Running cost is genuinely variable, so it is easy to justify not quoting it. That is also convenient, because the number is often uncomfortable and it surfaces after the contract is signed. Ontilus sizes all three lines against real transaction volume during technical scoping and gives the figure before signature, including how it grows.
You should expect the same from anyone you are evaluating. If a vendor cannot tell you what their system costs to run at your volume, one of two things is true: they have not built it at your scale, or they do not want you to know before you commit.
Line 1 — AI inference
What you pay the model providers. This is the line most people fixate on, and usually not the largest.
It scales with how much text goes in and out, not with how many outlets you run. A daily briefing across thirty outlets is not thirty times a briefing across one — it is one summarisation over a larger table. What actually moves this line:
- Frequency. Hourly analysis costs meaningfully more than a daily briefing, and is rarely worth it for decisions nobody makes hourly.
- Model tier per task. Classification, extraction and routing do not need a frontier model. Reserve the expensive tier for the reasoning that earns it.
- Context discipline. Sending an entire table when a pre-aggregated summary would do is the most common way this line quietly triples.
The single biggest lever here is architectural, not commercial: aggregate in the database, reason over the aggregate. Groups that send raw rows to a model pay for the same computation twice — once in tokens and once in accuracy.
Line 2 — Cloud infrastructure
Compute, database, storage and egress. This line does scale with outlets, because it scales with the volume of transactions being stored and queried.
The component that catches people out is egress, not storage. Storage is cheap and predictable; moving data out — particularly media — is metered on most platforms and grows with usage rather than with data volume. We have re-architected a media layer mid-project for exactly this reason, moving delivery to storage with unmetered egress so that growth in viewing stopped translating into growth in invoice.
Worth asking any vendor: which parts of my bill grow when my customers use the product more, as opposed to when I add outlets? Those are two very different curves.
Line 3 — Integration middleware
The connectors, sync agents and scheduled jobs that keep source systems flowing in. This line scales with the number of distinct systems, not with the number of outlets.
Twenty outlets on one POS is a cheaper integration surface than four outlets on four different systems. This is the line where a legacy on-premise system costs real money — not because the ingestion is expensive to run, but because it needs an agent deployed, monitored and maintained per site.
How the three behave as you grow
| Line | Grows with outlets? | Main lever |
|---|---|---|
| AI inference | Barely | Frequency, model tier, context size |
| Cloud infrastructure | Yes | Transaction volume, media egress |
| Integration middleware | No — grows with distinct systems | Consolidating source systems over time |
The practical consequence: adding your eleventh outlet on a POS you already integrate costs far less than adding your second distinct POS. Groups that understand this tend to make different decisions about which system a new outlet opens on.
What we commit to
Transparent, itemised running costs, confirmed at technical scoping and sized against your actual transaction volume — before you sign, including how each line grows as you add outlets. You will also be told exactly what you own in the codebase up front rather than after.
None of that is unusual to ask for. It is only unusual to be offered.
Dealing with this in your own group?
We answer scoping questions before there's a contract in sight — including the ones about cost and data handling.