Give AI a traceable source of truth about your brand.
Crawl public pages, structure brand facts and see coverage gaps without changing your website.
What Knowledge Base helps the team understand.
Crawl public pages, structure brand facts and see coverage gaps without changing your website.
Automatic fact extraction
Turn public product, service, pricing and trust pages into structured knowledge.
Coverage gaps
See which knowledge dimensions still lack usable facts.
Source traceability
Keep every extracted fact connected to the page it came from.
Keep every result connected to evidence and action.
The product explains the result, preserves its source context and makes the next review explicit.
The rules knowledge base follows
A feature list is easy to copy; the rules behind the numbers are not. Each of these is enforced in the product, and most of them were added after getting it wrong once.
| Rule | Why it exists |
|---|---|
| Every extracted fact stays linked to the page it came from. | A fact you cannot trace is a fact you cannot defend when a model repeats it wrongly. Traceability is what makes the knowledge base usable as evidence rather than as content filler. |
| Facts are grouped by source page, not listed one row per fact. | A ten-fact crawl of one page used to render as ten identical-looking rows. Grouping is what keeps the view readable as the crawl count grows. |
| Coverage is reported by knowledge dimension, and gaps are named. | Knowing you have 200 facts tells you nothing. Knowing you have none about pricing or returns tells you what to write next. |
| Facts are editable before they ground any generated content. | An extraction error that goes straight into published content becomes a wrong claim with your name on it. |
Move from summary metrics into the underlying question.
Sample data demonstrates the evidence depth of a formal project.
Visibility evidence
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Questions about Knowledge Base
Does this feature run from the public website?
No. Marketing pages explain the capability. Formal data collection begins only after a user enters the App and confirms the project scope.
Can snapshot results become part of this workflow?
Yes. A valid snapshot can be claimed as an initial sample, while onboarding still confirms markets, competitors and the formal monitored question set.
Are all metrics comparable across AI engines?
Core answer states can be normalized, but citations, search assistance and answer formats still need engine-specific evidence.
How often is the data refreshed?
Measurement runs on the schedule your plan allows, and monitoring quota is shared at the account level. Alerts require two consecutive runs to confirm, so model sampling noise does not become a false alarm.
Can the original AI answer be inspected?
Yes. Every result drills down to the answer that produced it, question by question and model by model, together with the citations found in that answer.
What happens when a model is unavailable?
That run is marked partial rather than being silently filled in. The remaining engines still complete, and the gap stays visible in the result.
Put Knowledge Base into a complete GEO workflow.
Create a project, confirm your market and start measuring the questions that matter.