Detection scores aren’t evidence: moving from 'AI or not' to verifiable provenance

The phrase “AI or not?” is becoming the wrong question. The right question is: can you prove origin and integrity in a way that can be audited?

Detection models are useful — but they’re probabilistic, they drift as generators change, and they often fail under heavy editing. In high-stakes scenarios, teams need something closer to a receipt than a hunch.

Provenance systems focus on verifiability: a proof signal embedded into the media (or attached as a signed manifest), a stable identifier, and a trail that can be checked later by independent tools.

For platforms and enterprises, the operational requirements look like this: fast checks, clear evidence, predictable failure modes, and privacy-aware logging. You need to answer “what is this file, where did it come from, and what changed?” without relying on one vendor’s black box.

That’s why DeadMark is designed as a free SDK: it can be embedded by any generator or exporter. DeadDetect is a paid verification API that returns presence, UID (when recoverable), confidence, and evidence — built for scale and enforcement workflows.

When you build for provenance, detection becomes a supporting signal instead of the single point of failure.