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Research & Academia

Research Integrity Verification

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The Problem

AI insights need verification, not just generation

The flood of AI-assisted research demands rigorous verification. Peer review is overwhelmed. Replication crises persist. AI-generated insights require new forms of validation.

Peer Review Backlog
Journals can't keep up. Months-long delays. Quality suffers under volume.
Replication Crisis
Published findings fail to replicate. Methodology questions persist.
AI Hallucination Risk
AI-generated analyses can contain plausible-sounding but invalid conclusions.
Citation Integrity
Fabricated citations, misrepresented sources, and broken evidence chains.
The Solution

Every research insight verified and traceable

Aequitas provides the verification layer that AI-assisted research needs to be trustworthy.

Logical Consistency Check™
Validates that conclusions follow from premises. Detects circular reasoning.
Statistical Validity Audit™
Verifies that statistical claims are properly supported by methodology.
Evidence Chain Verification™
Traces every claim to its supporting evidence. Flags unsupported assertions.

See It In Action

See how claims connect to evidence and how evidence supports conclusions. Red highlights weak links.

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TRY IT: Click any node to see supporting evidence or dependent claims

Real-World Applications

UseCases

See how organizations transform their operations with transparent AI governance

01

Pre-Submission Review

Verify research integrity before journal submission.

BeforeDesk rejection due to methodology issues caught late
AfterIssues identified and resolved before submission
02

Grant Proposal Analysis

Strengthen proposals by identifying logical gaps.

BeforeProposals rejected for unclear reasoning or methodology
AfterBulletproof arguments with verified evidence chains
03

Literature Review Validation

Ensure systematic reviews are complete and unbiased.

BeforeMissing key studies; publication bias undetected
AfterComprehensive, verifiable literature synthesis
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Aequitas caught a circular reasoning pattern in our analysis that three peer reviewers had missed. It saved us from a very public correction.
Principal Investigator
Computational Biology Lab•R1 Research University

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