Extend Introduces Verify, a Document Fraud Detection API that Builds Trust into Document Pipelines
Verify detects signs of document tampering and AI-generated fraud, helping businesses trust the documents their AI agents act on and deploy those agents confidently in the real economy.
LAS VEGAS, October 19, 2026--Extend today at Money20/20 USA announced Extend Verify, a document fraud detection API that helps developers and AI agents assess the integrity of documents before using them to make decisions.
Much of the work businesses want AI agents to perform begins with a document:
A bank statement supports a lending decision
An invoice initiates a payment
Receipt substantiates an insurance claim
Today, companies rely on teams of human reviewers to catch document fraud. But AI has made forgeries that are imperceptible to the human eye extremely easy to produce. When fraud escapes review to inform a loan, insurance claim, or background check approval, it can cost a business millions of dollars.
Giving agents greater autonomy means enabling them to cross that trust barrier. With Extend Verify, we're expanding our all-in-one document processing platform to assess document integrity, so your agents can flag suspicious inputs before acting on them.
"Businesses want to move beyond agents that search documents to agents that help get work done in the real economy," said Kushal Byatnal, CEO of Extend. "That requires trust in the evidence those agents act on. Verify helps developers build document integrity into their pipelines to prevent fraud-related losses, mitigate the difficulty of human review, and scale up agent deployments."
Document integrity built into the pipeline
Extend Verify examines visual content, file structure, and revision history, combining specialized models, forensic checks, and agentic analysis to identify suspicious signals. It checks for signs of:
AI-generated documents: Fabricated documents designed to resemble legitimate records.
Localized AI-tampering: Changes to specific fields or regions within an otherwise genuine document, down to single character edits.
Conventional digital editing: Patched text, image overlays, and other alterations made with PDF editing software.
Post-signature changes: Evidence of changes made after a document was digitally signed.
Verify returns detected signals, risk assessments and scores, explanations, and traceable evidence. Businesses can use those findings to determine which documents require further review.
Verify performance
Document fraud detection needs to catch suspicious inputs without overwhelming teams with alerts on legitimate documents. In a challenging benchmark evaluation, Verify accurately detected 96.3% of fraudulent documents at a 4.0% false-positive rate.