Data & market research

We turn assumptions into evidence—and say where it stops.

Independent research on markets and business decisions. Rules written before the data is opened, a slice of history sealed until the end, and failures kept on the record.

pre-registeredheld-out samplesneutral baselineshuman × AI
observationassumptionwhat the data shows (±1σ)
Fig. 1A claim is a line someone draws before looking. Evidence is the band the data actually occupies. The gap between them is the work.Illustrative figure · synthetic data · no measured result.
How we work

Three rules that make a result worth reading.

Not ceremony. Three gates that stop a convenient story from dressing itself up as evidence.

GATE 01

Pre-registered

Definitions, pass criteria and measurement are written down before the data is opened. If the bar moves after seeing results, the test proves nothing.

GATE 02

Held-out sample

A slice of history is sealed during development and opened once, at the end. It is the only honest way to know whether a finding survives outside the room it was born in.

GATE 03

Failures stay on the record

Rejected ideas are kept with the reason they failed. A map of dead ends is an asset—it stops the same money being spent twice.

Speed is not the achievement. With modern tooling, testing is cheap—which means coincidences that look like discoveries are cheap too. The guardrails are the product.

What we do

Five things, done properly.

Different assignments, one discipline: make the question explicit, preserve the trail, and keep the limit beside the answer.

  1. 01 · Research

    Market & strategy testing

    Does the rule actually work? We define pass criteria in advance, test against a neutral baseline, and report the limits alongside the result.

  2. 02 · Behaviour

    What people do, not what gets reported

    Which promotion truly lifted sales. Which signals precede a customer leaving. Whether field activity matches what was written down. Whether a long-standing rule still holds in recent data.

  3. 03 · Dashboards

    Live data dashboards

    Working instruments, not screenshots: live feeds, automated checks, and interfaces built so a non-technical reader can act on them.

  4. 04 · Automation

    Research automation with AI

    Pipelines where AI does the labour and a human keeps the judgement—with the guardrails that stop speed from producing nonsense.

  5. 05 · Audit

    Leakage & error detection

    Money leaves a business quietly: approvals made outside policy, assets idle but still carried on the books, figures that quietly stop reconciling. We rebuild the numbers from source records and show where they diverge—with the trail attached.

Selected work

Built from real systems.

These are sanitized views of working research and operating systems—not invented demo data. Identities, private figures and proprietary logic are omitted from the public build.

Field study · public case · n = 1 · not causal

When an agent became “gun-shy”

A four-day behavioural shift in a persistent AI-assisted research system, reconstructed from timestamped logs. Reported as one field observation—not a causal result—with competing explanations left intact.

timestamped eventlanguage ≠ measured actionalternatives kept open
System · real snapshot · 02 Aug 2026

A working memory that compounds

The live graph scans notes, research, tools and routines into one provenance-aware network. The counts shown are a dated system inventory; private node contents are not part of this page.

1,118 nodes1,841 links8 source families
Fundamentals · public source

Following each 100 units of revenue

A real annual-report chain, normalized so the business structure is visible without publishing a company identity. The private receipt maps every displayed index back to its filed source line.

audited sourcenormalizedidentity omitted
Operating system · anonymized

A private dashboard with receipts

One source of truth, explicit reconciliation and visible exceptions before a human call. The architecture is real; company identity and every operational figure remain outside the public source.

1 source of truth3 control states0 silent overrides

Public build policy · system-inventory counts and public-filing indices only · no client identity · no private operating figure · no trading data · no proprietary source code

Human × AI
“AI does the labour. A human asks the question, makes the call, and carries the responsibility.”

Most setups invert this—asking a model for judgement while a person does the grunt work. Run the right way round, the gain is not just speed: it is being able to test the boring, unglamorous questions that nobody had hours for before.

Contact

Start with one question.

Send the question you want settled. If it cannot be answered honestly with the data available, we will say so before any work starts.

[email protected]

Working notes on Instagram