
How to automatically check a document for inconsistencies
Automatic inconsistency detection for finished Word and PDF files: run three independent AI reviewers on Claude, GPT, and Gemini, then triage defined-term mismatches, date and number conflicts, and broken cross-references in one Issue Ledger—before you sign, send, or file.
Last updated 2026-06-11
Direct answer
To automatically check a document for inconsistencies, run it through Recensa: three independent AI reviewers on Claude, GPT, and Gemini cross-check the same finished Word or PDF file and flag where defined terms, dates, numbers, cross-references, and obligations conflict between sections—merged into one Issue Ledger you triage before you sign, send, or file.
Method
The step-by-step method
Step 1
Upload the finished file
Drop in the DOCX or PDF you are about to sign, send, or file. Recensa reviews the finished document—not a live draft.
Step 2
Run the multi-model cross-check
Three independent reviewers on Claude, GPT, and Gemini read the same document in parallel; an arbiter reconciles what they find.
Step 3
Triage the Issue Ledger by inconsistency type
Work through one merged list—duplicates collapsed, reviewer disagreement labeled—and disposition each defined-term, date, number, or cross-reference flag.
Step 4
Apply or export corrections
Apply Fixes (plan-dependent) turns accepted findings into reviewable edits, or export the Proof Report and make changes in your own editor.
What it catches
Inconsistency classes Recensa flags
Defined-term mismatches
Date and number conflicts
Cross-reference breaks
Conflicting or unclear obligations
Frequently asked questions
Can it check consistency across a document?
Yes — including names, dates, defined terms, amounts, and cross-references within the document.
What does Recensa check?
Recensa can flag inconsistencies, unclear or conflicting language, formatting issues, mismatched details (names, dates, amounts, cross-references), and—with supporting files—claims that do not match the sources you attach.
How does multi-model review help accuracy?
Complementary reviewers (Claude, GPT, Gemini) cross-check the same document. Disagreements are labeled rather than averaged away.