Why is fact-checking important for AI citations?

AI systems prioritize accurate, verifiable information. Content with factual errors is less likely to be cited. Our YMYL fact-checking ensures your content meets the high accuracy standards AI systems expect.

What is the two-tier verification system?

Tier 1 achieves 95% accuracy for precise data like statistics, dates, and quotes. Tier 2 achieves 85% accuracy for narrative claims and general statements. This dual approach balances thoroughness with efficiency.

Factual trust review before publish

Fact Checking

Review factual trust before publish

Run a final factual review on pages that matter so AI and readers see stronger, more trustworthy content.

I'm Veritas, your Trust Guardian. AI models heavily penalize inaccurate content — one wrong claim can destroy your citability. I run two-tier verification on every factual claim: precise data gets 95%+ accuracy checks, narrative claims get 85%+ validation. I find sources, flag risks, and protect your credibility.
Veritas

The problem

High-stakes pages cannot rely on best effort review

When a page carries commercial, regulatory, or trust sensitivity, factual mistakes are more than an editorial issue. They damage authority.

Teams publish under pressure and factual review gets rushed

YMYL or trust-sensitive pages need a repeatable verification layer

Manual review creates bottlenecks and inconsistent standards

Risky sections are hard to prioritize without evidence

Final pass

for factual confidence before publish

Workflow

How Fact Checking works

Review the page section by section

Inspect factual statements and check whether support is strong enough for publication.

Flag the highest-risk issues

Prioritize the sections most likely to damage trust if they stay unresolved.

Ship with a cleaner review trail

Give the team a clearer verification record before content goes live.

What you get

A factual review layer for important pages

Built to support editorial confidence before publication, not after a problem appears.

Factual review pass

Check whether key statements are supportable and current.

High-risk sections

Surface the parts of a page that deserve manual review first.

Source coverage view

See where supporting evidence is present and where it still feels thin.

Publish checklist

Move from scattered review comments to a cleaner go-live process.

Methodology

Trust review for factual confidence

Fact checking combines sourcing, claim review, and risk prioritization so important pages ship with stronger trust signals.

Princeton KDD 2024

Evaluation framework grounded in peer-reviewed research from Princeton University.

Proprietary data

The system improves with every graph and every citation outcome.

Protect authority before the page goes live

Use factual review as the final trust layer before shipping rewrites and updates.

Next in the pipeline

Source Discovery Claim Verification Citation Tracking

Fact Checking

Review factual trust before publish

Run a final factual review on pages that matter so AI and readers see stronger, more trustworthy content.

I'm Veritas, your Trust Guardian. AI models heavily penalize inaccurate content — one wrong claim can destroy your citability. I run two-tier verification on every factual claim: precise data gets 95%+ accuracy checks, narrative claims get 85%+ validation. I find sources, flag risks, and protect your credibility.