Straight answers
The objections I would raise if I were you.
A site full of confident copy earns a healthy amount of suspicion, and this one has more confident copy than most. So here are the hard questions: the ones a CFO, a referee and a producer would each press on, answered by me, including where the answer is "not yet."
For owners & operators
The questions a CFO asks
If you are about to spend money with us, these are the objections worth pressing. I have written the answers myself, because a CFO does not want them from a marketing department.
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You show no client savings figures. Why should I believe you can do this?
I would rather you did not take my word for it. Some of the hard parts are open source and you can read them today: orhof, chachaml, the book. The Rainbow repository is not published yet, and the page that describes it says so. A worked sample of the audit findings is published on a synthetic company, so you can judge the thinking before you pay for it. And the first step is a fixed-price audit that can end in "do not build", which I have watched happen and which nobody enjoys, least of all the person who wanted to build. We do not publish client margin numbers because they are the client's to disclose, and most clients will not. I could estimate them. But the first CFO to check one estimate against the client would be the last CFO to read this site, and that trade is not worth a paragraph.
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Every company says it is honest. What stops this site drifting into the usual overclaiming?
Machinery, because I do not trust intent to survive a year of edits, including my own. Every quantitative claim on the site resolves through one facts file that records where the number came from and who owns it, and anything marked unconfirmed does not render at all. A build check compares figures that appear in more than one place against that file and fails naming the file and the line. A second check holds a list of claims that were wrong once and must not come back, twenty of them as I write this, each carrying its reason. The counts on this page and on the validation page are computed from the collections when the site builds, so nobody can leave one stale by forgetting to update it. None of this guarantees good faith. But it makes drift expensive and visible, and you can check visible.
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How is this different from a normal software agency or a big consultancy?
An agency sells you build capacity. A big consultancy sells you a deck and a junior team, and I have been on the receiving end of both. We sell a sequence that reduces uncertainty: find the decision, prove a better method on your data, and only then build, with the same senior people from the first meeting to the last. So the money follows the evidence, and if the evidence says the software is not worth building, the audit ends there. You have still bought something. The certainty not to spend is usually the cheapest thing we sell.
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What exactly do I get for the €15k audit, and how fast?
In two to three weeks: a decision map, an economic baseline, a cost-to-complete forecast on your own projects, a ranked shortlist of interventions, and an explicit go, reshape or stop recommendation. The sample audit page shows the full shape of it, and I would read that before reading anything else on this site. The fee is creditable against a larger engagement if you proceed.
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We already have a data-science team. Why you?
Then you are who we work best with. We bring operations-research, formal-methods and product-engineering depth, and we turn analysis into an operated system. Your team brings domain knowledge and continuity, which we cannot supply and would not pretend to. The test is simple: does the combined team reduce the important uncertainty faster than yours alone? If it does not, the audit says so and the engagement ends there, and your team keeps the baseline we built.
For researchers & engineers
The questions a referee would raise
I would rather you attacked the work than admired it, and I think a referee would start with these three.
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Is the "lab" research, or marketing dressed as science?
Judge it by its epistemics. We preregister a falsifier before opening a result, keep negative results as results, separate a validated computational claim from a general-method claim in the same abstract, and state that the trusted kernel's soundness is argued informally and is not machine-checked. The OR library is open source and readable. The prover is written and licensed but not published yet, and the de-censoring artifacts are reproduced internally, and each page carries that status. External replay is the bar we are moving to. We have not reached it, and I am not going to write as if we had.
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You benchmark against your own solver on tiny synthetic instances. So what?
Correct. The speed-ups are against an internal baseline on small frozen synthetic populations, and a tuned external solver plus a runtime-versus-instance-size curve are the stated next step. What we claim now is exactness and a structure you can audit. We have not beaten a commercial MIP at scale. When we can claim that, the curve will be on the page, and until then the absence of the curve is the claim.
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The reviewer on every paper is the founder. That is not peer review.
Agreed, and so the label says "internal reviewer" and not something grander. Internal preregistration and reproduction are what we have today. Independent external verification is named on the site as the standard we are building toward, and I would rather name it as a gap than let a reader discover it as one.
Start with the decision
If you are not convinced
The fastest way past a fair doubt is a small, bounded test. Describe the decision you are unsure we could improve, and I will answer whether we can, and how we would prove it.
Who you deal with
If you would rather ask a person than read a page, I or a partner will take the call and answer the same way. Work is confidential and unattributed by default, and no client of ours appears anywhere without written permission.