Enter the same three facts as they appear on each third-party profile (Crunchbase, LinkedIn, G2, a registry). Leave a cell blank if the profile does not state it. Nothing is uploaded.
Drift across profiles fragments your entity node and erodes algorithmic confidence. Fix every conflict at the Entity Home first, then correct outward. Dates compare on the year.
Why consistency is the lever
When your Entity Home asserts a fact, crawlers look for that exact fact elsewhere. If registries, Wikidata and directories echo it, confidence rises and you earn stable nodes and Knowledge Panels. If they contradict, the node fragments and generative models start improvising, aligning your legal name across nine directories is the highest-leverage afternoon in the whole project.
This checker flags where your profiles disagree with the canonical values. It runs entirely in your browser.
How to use it
- Enter your canonical facts (founding date, HQ, name).
- Paste the values from each external profile.
- Fix every conflict the checker flags against your Entity Home.
Frequently asked questions
Why does fact consistency matter for AI?
When your founding date, name or HQ differ across Crunchbase, LinkedIn and your site, engines see several weakly-linked entities instead of one strong one. Consistent facts across profiles are what let a model resolve and trust you as a single entity.
Which facts should match everywhere?
The identity-defining ones: legal and brand name, founding date, headquarters, key people and category. The checker compares each against your Entity Home and flags drift so you can reconcile the outliers.
Is the Fact-Consistency Checker free to use?
Yes. The Fact-Consistency Checker is completely free, with no sign-up, no usage limits and no watermark on the output.
Is my data private?
Yes. The Fact-Consistency Checker runs entirely in your browser. Nothing you paste or enter is uploaded, stored or sent to any server.
Related tools and reading
Keep going with the playbooks and tools behind this one.