Education
Academic integrity work, handled fairly
TraceMark AI gives schools and universities a structured way to examine submissions without turning a probability into an accusation.
Capabilities
What your team gets
Department workspaces
Separate faculties, courses and cohorts with their own members and retention rules.
Reviewer roles
Instructors submit; designated reviewers decide. Auditors can see everything and change nothing.
Case management
Track each analysis through Pending Review, Reviewed, Needs Investigation, Cleared or Inconclusive.
Internal notes
Reviewers record context — drafts seen, interviews held, prior work compared.
Exportable reports
Produce a record suitable for an integrity panel, including the limitations statement.
Fairness guardrails
Interface language and report text never claim proof of authorship.
Workflow
A review process you can defend
Every analysis moves through a documented path with an accountable reviewer at the end.
- 01
Submit
Instructor pastes text or uploads the document from the LMS export.
- 02
Analyze
Signals are computed and flagged passages are highlighted with explanations.
- 03
Review
A trained reviewer weighs the evidence against drafts, history and a conversation with the student.
- 04
Decide
The case receives a status and a note, and the report is archived.
Detection output is one input into an academic integrity process — never the process itself. TraceMark AI is built to make that boundary explicit to every person who opens a result.
AI detection is probabilistic. This result does not establish authorship and should not be used as the sole basis for academic, employment, disciplinary, or legal decisions.