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The category, compared

How we differ from population-simulation vendors.

A category of AI vendors now sells large-scale "simulation of people" to enterprises and governments: striking claims, gated demos, no published method. This page compares approaches, not companies — on the axes any serious buyer should test every vendor against, including us.

What actually separates the two approaches

In one sentence: a gated simulation vendor asks you to trust a result you cannot inspect, while LEXUN publishes the method, shows the error bars, keeps a public calibration record and hands you a way to reproduce the answer yourself. The nine rows below are the axes where that difference stops being rhetoric and becomes something you can test — each one is a question you can put to any vendor, including this one, and expect an artefact in reply rather than an assurance.

AxisTypical gated simulation vendorLEXUN
Published methodUndisclosed; "proprietary simulation"Full methodology public on the Accuracy Centre; model maths documented per domain in the method guides
Error barsPoint claims ("we predicted X within 0.n%")Every probability shown as a band; binomial standard error disclosed; false precision refused by design
Calibration recordNone publishedPublic Brier-scored record, computed only from resolved outcomes — published from an honest zero on day one, growing only as reality answers
ReproducibilityNot offeredSeeded and versioned: identical inputs reproduce identical outputs — verify in your browser now
Tamper evidenceNot offeredEvery result is sealed with a SHA-256 hash over its canonical bytes and the audit record is hash-chained — check a result without trusting us
Stated moatScale, data access, proprietary methodScoring, receipts and elapsed time — set out in full, including what is not a moat, on the defensibility page
AccessDemo request, sales-gatedFree and in your browser today — no Key needed to run a decision; a LEXUN Key is required to save one, and a Key is a free passcode that encrypts your record on your own device rather than an account on ours
Refusal behaviourAn answer for everything"Insufficient evidence" is a real output; out-of-scope domains are declined, not improvised
Data handlingYour scenario data on their serversLocal-first: simulation inputs and saved decisions stay in your browser; the optional Copilot sends only what you type into it and a filtered result summary — architecture, plainly
Rather than argue the first two rows, we built them into a page you can press: the same simulation delivered as a glass box and as a black box. One run, two panels, live in your browser. Fairness note: gated vendors may have strong internal validation we cannot see. That is precisely the point — a buyer cannot act on evidence they are not shown. Apply this table to us too: every LEXUN row above links to the artefact that proves it.

The questions to ask any simulation vendor

  1. Can I see the calibration record, and who computed it?
  2. What does a forecast look like when you are uncertain?
  3. Can I re-run yesterday's prediction and get the same answer?
  4. What happens when I ask something outside the model's competence?
  5. Where does my data live while you simulate with it?

We publish our answers. Demand everyone's.

What we refuse to fake — and why that wins

A comparison that only flatters its author is marketing, so here is our position, plainly — every line of it a choice, not a gap. Our public calibration record started from zero on day one, and the Accuracy Centre printed that zero in the open: that is what an honest record looks like at the start, and it is exactly why it will be unanswerable later — a record that started earlier can be caught up with; one that started honest cannot be faked. We have not found a published, scored forecast record among the vendors we reviewed; if one exists, we will link to it here. Our coverage is three decision domains — business runway, career change, major purchase — built deep rather than a catalogue built thin: versioned models, stated weaknesses, reproducible to the byte. And when a question sits outside them, the engine says so instead of improvising — the refusal is the feature. An engine that answers everything is an engine whose answers mean nothing.

Which approach fits which buyer

Gated population simulation is built for organisations buying scale: large panels, bespoke modelling engagements and a supplier relationship with account managers attached. LEXUN is built for the person or small team facing one consequential decision this week whose reasoning has to survive scrutiny afterwards — from a board, an auditor, a co-founder, or their own future self reading it back in a year. The two are not really chasing the same budget. They are chasing the same claim: that a number on a screen has earned the right to be believed.

Questions people actually ask

How is LEXUN different from asking a chatbot?

A general-purpose assistant generates a plausible answer; LEXUN's numbers never come from language-model intuition. Every probability comes from a seeded, versioned simulation you can reproduce bit-for-bit, every result is frozen with a criterion and a date, and reality grades it afterwards on a public register. The honest cost of that discipline: LEXUN answers far fewer kinds of questions.

What should I look for in any decision or prediction tool?

Five things, and they apply to LEXUN too: can you reproduce a result exactly; does every number have a source or a stated assumption; are forecasts frozen before outcomes are known; is there a scored track record rather than testimonials; and does the tool ever say 'insufficient evidence'. A tool that fails these tests is asking to be trusted rather than checked.

Can LEXUN tell me which stocks or crypto to buy?

No, and it refuses rather than guessing: no financial-market model is released, no licensed market data is held, and an invented probability about an asset price is the exact failure this product exists to prevent. What it can run is the resolvable question underneath: whether your cash or buffer survives if the amount you are thinking of investing were lost — a released, seeded model with a receipt. Decision intelligence, not investment advice.

Is what I type used to train an AI?

No. The simulation runs on your device, and the sentence you type into the homepage box is parsed there and never transmitted. The one exception is the optional Copilot in the workspace: it sends what you deliberately type into it to the AI provider, only when you press its button, and result tools send only a filtered result summary — none of the financial figures you entered into the engine. There is no analytics script to smuggle it out — the privacy notice and the network tab agree. The optional assistant is the one clearly-labelled exception, and it says so before you use it.

Where is LEXUN weaker than the alternatives?

Scope, breadth and sample size. Three released models, not three hundred; verified evidence covers the United Kingdom only; reference data is bundled dated snapshots, not live feeds; and the resolved-outcome sample is still below the ten-outcome minimum per domain, so no accuracy percentage is published yet. These limits are stated on the product because pretending otherwise would cost the one thing LEXUN has: a record you can check.