How Truely thinks

Everyone has the same data. The reading is the hard part.

Truely turns official UK datasets into a plain-English reading of a place — what's true now, which way it's moving, and how sure we are. This page shows exactly how that reading is built: where each signal comes from, how it's weighed, how confidence is scored, and where interpretation stops.

Reads, not tables. A figure tells you what. We tell you what it means and whether it should change your decision.
Every reading carries its confidence, its sources and its recency — so you can see how far to trust it.
We name our limits. Where the data can't support a conclusion, we say so rather than inventing one.

The pipeline

How a reading is built

Every reading on Truely follows the same path, from raw public records to a single plain-English line with a confidence attached. Nothing is generated from thin air — each step is deterministic and traceable back to a named source.

1

Official records

We start only with published UK government and regulator datasets — HM Land Registry, MHCLG, Ofsted, police.uk, the Environment Agency, DEFRA, Ofcom, Ordnance Survey and two dozen more — under the Open Government Licence. No scraped opinions, no proprietary black boxes.

2

Normalisation

Each signal is placed on a common scale — most as a percentile against every other covered postcode in England — so "£1,028 council tax" becomes "cheaper than 99% of the country". That's what makes one area comparable to another.

3

Cross-signal comparison

Signals are read together, not in isolation. Low crime beside improving schools beside rising broadband reads differently from low crime beside falling school rolls. The relationships between signals are where the interpretation lives.

4

Temporal analysis

Where we hold history — deprivation back to 2015, Band D council tax to 1993, crime over a rolling 24 months — we read the direction of travel, not just the snapshot. A place improving for eight years reads differently from one that just dipped.

5

Weighing & interpretation

Signals are weighed by relevance to the question being asked — a family lens leans on safety and schools, an investor lens on fundamentals and affordability. The weighting is documented, never hidden, and the same inputs are shown alongside the conclusion.

6

Confidence scoring

The final reading carries a confidence level set by how many signals were present, how recent they are, and whether they agree. A reading built on four corroborating, current datasets is labelled differently from one resting on a single older figure.

Provenance

Where every number comes from

Not all data is equal, and we don't pretend otherwise. Every figure on Truely falls into one of four tiers — and we tell you which, so an observed fact is never confused with a modelled estimate.

Observed

Published directly by an official source. The strongest tier — we are simply reporting the record.

e.g. Band D council tax, recorded sale prices, Ofsted ratings, flood zones.

Derived

Computed deterministically from observed data — a ranking, a percentile, a distance. Reproducible from the inputs.

e.g. "cheaper than 99% of England", nearest-school distance, crime density.

Estimated

An informed approximation where no single official figure exists. Always shown with the evidence behind it and a confidence label.

e.g. property valuation, shown with every comparable sale it rests on.

Interpreted

A plain-English reading composed from the tiers above using documented rules. It explains; it never overrides the underlying data.

e.g. "transitional urban growth rather than decline", direction-of-travel verdicts.

Confidence

What "high", "medium" and "low" actually mean

Confidence isn't decoration. It's set by a simple, consistent rule: how complete the evidence is, how recent it is, and whether the signals agree. Here's exactly what each level means.

High
Corroborated by multiple current, stable datasets that agree. The conclusion would hold even if one source were set aside. Most observed and derived figures sit here.
Medium
Partial or mixed evidence. A clear trend in most signals but with gaps, an older input, or one signal pulling the other way. Directionally sound; worth a second look before acting.
Low
Directional inference only. Thin, sparse, or single-source evidence. We surface it because it's better than silence — but we flag it plainly so you don't lean on it.

A worked example

Reasoning, with the contradictions left in

Real places send mixed signals. A reading that smooths every contradiction into tidy certainty isn't intelligence — it's marketing. Here's how Truely holds supporting and conflicting evidence together, and lands on an honest read.

"Is this area getting better or worse?"

An inner-urban postcode, illustrative of the pattern.

Supporting signals

School performance improved over three years
Gigabit broadband now near-universal
Violent crime below the regional average

Conflicting signals

Total recorded crime up modestly year-on-year
Affordability worsening faster than incomes

"Improving, with pressure. Schools, connectivity and serious-crime trends point to a strengthening area — but rising overall crime and worsening affordability suggest transitional growth rather than a settled, low-pressure neighbourhood. Weigh it as a place on the way up, not one that's already arrived."

Confidence: Medium–high Recency: all signals within 24 months Limitation: no long-term migration data to confirm the direction

Auditability

Every score, traceable to its inputs

There is no black box to take on faith. Each lens score is a transparent weighted composite, and every score carries its evidence: each input, its weight, its value, and how it reads against England. You can see exactly why a place scores the way it does — and so can an auditor, a lender's risk team, or a regulator.

Shown on every reading. On the intelligence page each of the five lenses expands to its weighted inputs — a plain-English read per signal, the confidence (an honest "N of M signals" count), and a link to the official source. Nothing is asserted without its working.
Machine-verifiable. The same evidence is in the API: GET /api/v1/intelligence/{pc} returns each lens's score, band, confidence and the full evidence array — every weighted input and how it reads vs England. Integrators can audit a score programmatically, not just trust a number.
Reproducible & versioned. Scores are deterministic functions of dated public records — the same inputs always produce the same score. When a methodology changes it changes for everyone at once and is noted in the changelog, never silently re-weighted behind the scenes.

The limits

What Truely does not do

An intelligence layer earns trust as much by what it refuses to claim as by what it shows. These lines are deliberate.

We don't predict the future with certainty. Where we describe direction of travel, it's a reading of past and present data — not a forecast dressed up as fact.
We don't give regulated advice. Truely provides signals to inform your own decisions — not financial, legal, mortgage or investment advice, and not a valuation you can lend against.
We don't invent missing data. If a dataset doesn't cover an area or a figure isn't robust, the reading says so rather than filling the gap with a guess.
We don't hide the method. Every score shows its inputs and weighting; every figure links to its official source. If you can't inspect it, we shouldn't claim it.

The full source list and refresh cadence live on the methodology page; live dataset status is on the status page. When the reasoning changes materially, we record it in the changelog.

See it on a real postcode →