Onboarding runs on trust in documents — identity, eligibility, credentials. Docurensic checks the paperwork new hires and contractors submit for forgery and AI-generation before it becomes a problem.
A constructed example — not a real customer file — showing the kind of finding Docurensic surfaces on a scanned credential.
A rectangular region around the conferral year shows compression and noise unlike the surrounding scan — the signature of a pasted-in edit.
Image forensics · ELA + noise · strongThe page image lacks the sensor noise and off-white cast of a genuine scan, suggesting a document composed digitally and dressed as one.
Provenance · indicativeCredential and identity fraud at onboarding is quiet and costly. A diploma that was never issued, a W-2 with an edited figure, or an ID that was assembled in an editor can all look convincing at a glance.
Docurensic verifies the documents the way an examiner would, extracts the identifiers, and can link a new hire's documents into a case when the same details show up somewhere they shouldn't.
Five layers, one verdict. Every document runs through security, forensics, reasoning, validation, and external lookups — see how the engine works.
Document-specific guides: spotting a fake pay stub · checking a proof of address.
It inspects the file for tampering, validates that the fields are well-formed and consistent, and flags documents that were altered or generated rather than issued.
Yes — forged and AI-generated credentials are exactly the kind of document the forensic and content-trust layers are built to surface.
You control storage — Store or Storageless — and documents are encrypted if kept. Full detail is on our Security page.
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