Notes on data, decisions, and practical AI.
Working notes from the team behind UK Crime Insights — what the data actually says, how to read it well, and where AI helps without overreaching.
Reading a UK postcode crime report
A walkthrough of every section of a postcode report — what each category count means and how to read the AI summary.
MethodologyPolice UK's open data: what's in it, what's not
Where the data comes from, the monthly release cadence, and the limitations every interpretation needs to acknowledge.
Crime data explainedAnti-social behaviour vs public order
The two most-confused categories in UK crime data — what each one actually covers, and why it matters for interpretation.
For estate agentsCrime data in property due diligence
How estate agents can use crime data well — what to surface for buyers, what to omit, and where it adds genuine signal.
For solicitorsConveyancing and crime data
When crime statistics are material in conveyancing, when they aren't, and how to handle client questions about safety.
InterpretationThe geography of UK crime reporting
Why some areas appear to have more crime than others — and how reporting density distorts apparent geography.
Worked exampleComparing two postcodes: a worked example
How to compare two areas honestly — the right denominator, the right time window, and what to look at beyond totals.
AI methodologyHow our AI safety summaries are written
What the LLM step in Crime Insights actually does — and the cases where it can mislead if you read it without the data.
AI methodologyWhy we don't predict crime with AI
A deliberate non-feature — what predictive crime models get wrong, and why we describe the past instead.
AI methodologyAn AI assistant or a dashboard?
A practical framing for B2B buyers commissioning AI work — when conversational beats visual, and when it doesn't.
AI methodologyEvaluating an AI prototype: a checklist
Eight questions a non-technical stakeholder can ask of any AI prototype to understand what it actually delivers.