Pasted & painted-over edits
Pixel-exact detection of rectangles pasted over an original — including the kind whose colour differs by 4 parts in 765 and is invisible to the eye.
DFDS examines invoices, tenders and certificates for tampering, pasted-over edits, AI generation and financial inconsistency — then explains the evidence in a report an officer can act on and defend.
Access is issued by an administrator. Contact yours to be invited.
Deterministic forensics first, AI second — so a finding can be measured, pointed at and defended.
Pixel-exact detection of rectangles pasted over an original — including the kind whose colour differs by 4 parts in 765 and is invisible to the eye.
Fonts a document never otherwise uses, revisions made after it was signed, and metadata that disagrees with the content.
Synthetic and re-rendered pages, flagged from generator fingerprints and visual review rather than a hunch.
Totals that don't follow from their line items, tax that doesn't compute, and summary figures that contradict the detail rows.
Three steps — and a person decides at the end of them.
Upload it, or let a scheduled workflow collect it from Azure Blob, S3, FTP or SFTP the moment it lands.
Metadata, per-page pixel forensics, structural checks and an AI review run together — every page, every embedded image.
A risk score with findings, annotated evidence images and a downloadable report — routed for human validation before anything is accepted.
A fraud finding is worth exactly as much as the evidence behind it.
Red = pixels exactly matching the pasted patch. Green = the surrounding element. They differ by 4/765.