Questions buyers actually ask.
Straight answers for enterprises and private equity sponsors. Each set comes from the page that covers it in full.
Enterprises
How is this different from AI staff augmentation or an embedded engineering pod?
A pod sells you capacity. You decide what to build, they build it, and the risk of building the wrong thing stays with you. We sell the decision itself: which steps of your workflow should become a model, which should become ordinary deterministic code, and which should stay with a person. In practice most of the system should not be AI, and a vendor paid per engineer per month has no reason to tell you that.
What is an Exception Ledger, and why does reading our documentation not produce one?
It is a written record of every real deviation from your documented process: how often each exception occurs, who currently absorbs it, and where the routing logic actually lives. That logic is almost never in the documentation. It is in one person’s head, and it only comes out when you watch the exception happen and ask the person handling it why they did what they did. A team working from your repository and a weekly status call does not do that, so it cannot produce the ledger: the information is not in the repository, and nobody volunteers the thing they have always just known.
How much of the system will actually be AI?
Less than you expect, and that is the point. The AI Boundary Map annotates each step of the workflow as deterministic code, genuine model judgement, or human approval. A typical result is that three of eleven steps need a model. Every step you move out of the model is cheaper to run, faster, and easier to audit, so the determinism ratio is a commercial number, not an engineering preference.
Do you replace our ERP?
No. We build on top of your existing systems, we do not propose replacing them, and we do not require a migration. This is a covenant, not a preference. A replatforming programme is the single largest career risk an operations or IT leader can take on, and it is almost never what the problem actually requires.
How does an engagement start, and how is it priced?
It starts with a free thirty-minute qualification call. From there the shape is always the same: a paid Mapping Sprint of five days, run alongside the people who do the work, which produces the Exception Ledger, the AI Boundary Map, an evaluation plan and a fixed-price build quote; then a fixed-price build scoped from what the sprint found rather than from a guess, with the first workflow in production in six weeks; then an ongoing run engagement once the system is live. Everything after the call is priced per engagement, and we quote it after the call rather than before, because the scope is a finding. If the sprint shows you nothing you did not already know, you do not pay for it.
When are you the wrong choice?
When you are large enough to staff a standing internal practice, hire it instead — embedded delivery is how you learn what to hire for, not a permanent substitute. When the problem is arithmetic rather than judgement, a rules engine or a spreadsheet will beat anything we would build, and it will cost less to maintain. And when no executive owns the outcome, the work stalls at the first approval boundary regardless of who builds it.
Private equity
Is this a substitute for hiring an AI Operating Partner?
No. It is the instrument that role needs before it exists, and the one it keeps using once it does. An operating partner covering a portfolio cannot sit inside every company for a week; a Mapping Sprint does exactly that, one portfolio company at a time, and hands back a written answer on whether there is anything worth building, what it would cost, and how much of it is genuinely AI. If you later hire for the role, the sprints tell you what shape of person to hire. If you already have, they are the diligence the role runs on.
Can you run this across several portfolio companies at once?
In sequence rather than in parallel. Each sprint is five days spent with the people who actually run the process, and that depth is the point, so we do not thin it out across three companies in the same week. What is repeatable is the instrument: the same five artifacts come out of every sprint, which makes the findings comparable across the portfolio even when the answers are different.
How does this fit inside a hold period?
The sprint produces its answer in five working days. If the answer is yes, the first workflow is in production six weeks after the build starts, with a monthly accuracy report from then on. We build on top of the systems the company already runs and never propose replacing them, because a replatforming programme is the one AI initiative that is guaranteed not to pay back before exit. The decision log is designed to be opened by an acquirer’s diligence team, not just by yours.
What does the sponsor actually receive?
Five named documents rather than a status deck. The Exception Ledger records how the portfolio company really runs, including the routing rules that live in one person’s head. The AI Boundary Map shows how much of the thesis is actually AI, step by step. The evaluation suite and its monthly accuracy report give you a number that goes into the board pack. The decision log makes every automated action defensible. The ERP-additive covenant is a written commitment that nothing gets replaced.
How much of the system will actually be AI?
Usually a minority of it. In one European manufacturer’s order-handling workflow that SUPALABS mapped step by step, three of eleven steps genuinely needed a model; the other eight were parsing, lookups, validation and routing that ordinary software does more cheaply, faster, and with an answer you can reproduce. That single engagement is not a statistic, but the shape repeats. Every step moved out of the model is cheaper to run and easier to defend, so the determinism ratio is a commercial number for a sponsor, not an engineering preference.
How is it priced, and why are there no client names on this page?
The thirty-minute qualification call is free. Everything after it is quoted per engagement and after the call, because the scope is a finding rather than an assumption: pricing a build before the sprint means pricing a guess. If the sprint shows you nothing you did not already know, you do not pay for it. Client names are never published because an embedded operator sits inside a portfolio company’s operation, and confidentiality is a condition of that access. What you can inspect instead is the method and the five artifacts every engagement produces.
Thirty minutes to find out whether there is anything worth mapping.
The call is free, and we will tell you if the answer is no. Bring one workflow that annoys you.