For academics who need to prove original scholarship.

The current model is adversarial: run a detector, flag the student, force them to defend themselves. That process is unreliable and damaging. AI detectors routinely produce false positives, and the burden of proof falls on the student.

Humanums flips that dynamic. Students opt in to capture behavioral signals while writing, then submit a certificate alongside their paper. The proof comes from the process, not from a probability score applied after the fact.

AI detectors have documented bias against non-native English speakers and writers with atypical prose patterns. Students who write in a second language or who have different cognitive processing styles are disproportionately flagged, even when their work is entirely original.

Process-based verification does not analyze the text itself. It watches how writing happens: keystroke timing, revision patterns, pause behavior. That makes it bias-resistant in a way that text-analysis detectors fundamentally cannot be.

No servers to deploy, no LMS integration required. Students write in the Humanums editor, certify their work, and share the verification link. The entire workflow lives in the browser.

Institutions can verify any certificate through the public verification page. Faculty can check a student submission in seconds without installing software, requesting admin access, or learning a new platform.