Two Different Machines
Let's be fair to Checkr before we take it apart: it is a good company at what it actually does. Checkr is a consumer reporting agency. Its product is the background report — an FCRA-governed document, ordered per candidate, assembled from SSN traces, national and county criminal searches, watchlists, and yes, a sex offender registry search, bundled together starting at $29.99 a report and rising to $94.99 for the full package. There is a consent flow, a candidate portal, a dispute process, an adverse-action workflow. If you are running formal employment background checks, that machinery is not overhead — it is the product, and Checkr builds it well.
But notice what that machine is shaped like: a report factory. A human orders a check on a candidate, paperwork happens, a document comes back, a human reads it. Every part of it assumes screening is an event — something that happens once, at hiring, with a file to show for it.
Registry screening inside a product is not an event. It is a function call. A caregiver marketplace wants to screen at signup, again at every booking, and continuously in between. A visitor-management system wants an answer while the person is standing at the desk. A platform wants to rescreen its entire population nightly, because as our guide to sex offender registry APIs lays out, registry data changes every single day across 57 independent government systems.
That is the machine Offendersearch, a national sex offender registry API, is: one synchronous endpoint over all 57 U.S. registries — 1.5 million records, re-read nightly — returning normalized, deduplicated, confidence-scored matches with per-source provenance, in roughly 142 milliseconds. No order form, no queue, no PDF to parse. Data in, structured answer out.
Once you see the two shapes clearly, most of the comparison resolves itself. The only real question left is which shape your problem is — and for registry screening specifically, it is almost never shaped like a report.