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Academic & Scientific Research

Researchers & journals

Reference, methodology, and dataset verification that protects research integrity from retraction risk.

The Problem

Generative AI produces confident-sounding but false references, misattributed findings, and fabricated experimental details. For researchers and journals, this threatens retractions, reputation loss, and integrity investigations.

Our Solution

We cross-check references, methodology claims, and data sources against published literature and original datasets. Our review ensures citations exist, support the claims made, and are accurately represented.

Bibliographic existence and relevance checks
Methodology and data-source verification
Retraction, predatory journal, and conflict screening
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Verification Report
Factual claims verified
Pass
Citations sourced
Pass
Human reviewer sign-off
Signed
Hallucinated references
Flagged
Audit-ready certification included