Demo 3 — Data / Analyst

18 minutes. For someone who wants to know what's in the dataset, how good it is, and what they could ask of it.

The thesis for this audience: the dataset is large and the coverage is honest about itself. Do not oversell breadth — sell the fact that you can tell verified from inferred, per row.

What's actually in it

TableRowsWhat it is
psc_stage10,774,730Persons of significant control — the ownership graph
company_employees6,848,125Employee counts + financial headline per company
ch_universe3,228,658The company universe — identity, SIC, status, filings
fact_candidates657,585Extracted financial facts awaiting corroboration
company_edges340,170Parent/subsidiary relationships
fin_* (16 tables)0The financial grid — built, empty. Be upfront.
All counts are COUNT(*) run today, not n_live_tup estimates. That distinction matters here — the autovacuum estimate on this box has been wrong by two orders of magnitude on at least one table.
1 · 5 min

Coverage honesty — lead with this, don't bury it

https://company.ukacq.comBAE SYSTEMS MARINE
"Most of the employee time-series is inferred rather than filed. We don't hide that behind an average — the label changes per row. If you're building a screen on employee growth, you now know which 8% you can stand on."
Volunteer the units defect before they find it. 551 of 8,365 companies with >100 employees show revenue under £100k — a units inconsistency in the source. That's 6.6% of large companies. It's filed with the data owner. Searching BAE SYSTEMS (OPERATIONS) shows one: 16,609 employees, "£7,103" revenue.
2 · 4 min

The ownership graph — the underused asset

Current limit: chain traversal is shallow — the immediate corporate owner renders, multi-hop traversal is not built. The data supports it; the query doesn't exist yet. Don't imply you can walk a full ownership tree today.
3 · 5 min

Classification — where the dataset is weakest

https://define-game.ukacq.com → tab 2, "Pick from the data"
"This is the honest weak point. We can count 3.2 million companies instantly and we can't yet slice them the way an analyst actually thinks. The fix is a ratified 7-axis taxonomy — sector, business model, offering, supply-chain tier, value-chain function, and three ownership facets — replacing one conflated code."
Why it matters to this audience specifically: the taxonomy work is the difference between "3.2M rows" and "a queryable universe". If they care about screening, this is the roadmap item to discuss.
4 · 4 min

What the scoring layer holds

https://select-game.ukacq.com
The caveat this audience will care most about: there is no human-authored reference set anywhere in this system. The 23 benchmark reports say "Screened by: Claude" in their own headers, and the reference scoring labelled with a person's name was a model one-shot they had shown as an example. We retracted that in writing on 2026-07-21. So no quality number from this layer is defensible yet — the arithmetic is verified, the judgement is unbenchmarked.

Questions this audience asks

QuestionHonest answer
"Can I export it?"Not verified — I have not tested an export path. Don't promise it.
"Is there an API?"Internal JSON endpoints exist behind the auth wall. No documented public API.
"How fresh is it?"Two iXBRL bulk loads registered (2026-06, 2026-07). Check the Sources block for the exact date before quoting one.
"What about non-UK companies?"Not yet. Everything is keyed on Companies House number. A scheme-agnostic identity layer is designed and unbuilt — that's what unlocks EU entities.
"Financial history depth?"Headline figures per company. The 16-table year-by-year grid is built and empty. Say built-not-populated.
"Can I get the raw data?"Commercial question, not mine to answer.