Expert-reviewed findings
Flagged cases become evidence that editorial and institutional teams can review and act on.
FigScan delivers AI-powered image integrity detection for duplication, manipulation, and plagiarism in research papers.


































Flagged cases become evidence that editorial and institutional teams can review and act on.
One workflow covers duplicated panels, transformed reuse, and figure-level irregularities.
Structured outputs reduce noisy alerts and support documented review decisions.
Identify cloning, splicing, deletion, and suspicious local alterations before review.

Compare figures and pages to surface duplicated panels, including transformed reuse.

Compare submitted figures with a broader scientific image index.

PDF or figure package.
Duplication and manipulation checks.
Evidence is triaged and validated.
Outputs are ready for follow-up.


Review figures before submission and keep a documented record for co-author review and submission readiness.
Support research integrity oversight and secure internal review with clearer documented evidence.
Give editorial teams a more consistent pre-publication screening workflow with decision-ready reporting.
FigScan screens for image duplication, transformed reuse, suspicious local manipulation, and panel-level similarity in scientific figures and manuscripts.
The platform is built for researchers, research integrity offices, institutions, and publishers that need reviewable evidence rather than a black-box alert stream.
Yes. FigScan can support comparison against a broader scientific image index in addition to within-manuscript screening.
Yes. Reports are structured for editorial decision-making, compliance documentation, and institutional follow-up.