Predictive analysis can help a task force decide where to look — which is useful, and easy to misuse. The line between the two isn’t drawn by the algorithm. It’s drawn by the standard you attach to it.
What a model can and cannot claim
Every model we deliver ships with a plain-language brief on what it can and cannot support: its inputs, its known limitations, and the questions it is not valid to answer. A hot-spot model can tell you where incidents have concentrated. It cannot tell you who will commit one.
Guardrails against bias
Historical data carries historical bias. We document where that risk lives in a given model and what we did to constrain it, so the output informs judgment rather than laundering old patterns into new decisions.
Where to look, never whom to suspect
Our firmest rule: we do not build tools for individual-level targeting or surveillance. Models inform where to look, never whom to suspect. That boundary is written into the deliverable, not left to interpretation.
Want to see the responsible-use standard in full? Request a quote and we’ll walk you through it.