Monitoring across several AI systems
The same question runs repeatedly across different engines. GeoTopX records each answer with its date, engine and version, because a single answer is not a measurement.
GeoTopX is the evidence and decision layer for brand visibility in artificial intelligence answers. Instead of reducing a variable answer to an isolated score, the platform preserves the context, states the limits, and ties every recommendation to the evidence behind it.
The same question runs repeatedly across different engines. GeoTopX records each answer with its date, engine and version, because a single answer is not a measurement.
How much of the conversation is yours and how much belongs to competitors, with the sample size and the run-to-run variation always visible beside the number.
A consolidated index per brand, product and category, always accompanied by the components that produced it. No number appears without the arithmetic behind it.
Who appears in your place, in what context, and backed by which sources. Comparison runs over the same questions and the same period.
Which pages were cited or observed alongside each answer, with the address preserved. You see what supports the answer, not only its text.
The tone your brand is described in and the subjects it sits next to, with the original excerpt available for checking.
What on your site helps or hinders reading by generative engines and search engines, item by item, with the test behind each conclusion.
Cortex maps the differences between models and estimates the likely impact of a change before you make it, always with the confidence level stated.
Every recommendation says what to do, why, and which evidence prompted it. None suggests an action without pointing at the data behind it.
From the observed answer to the final report, every step stays reviewable: preserved artifact, normalized observation, metric, recommendation.
Most tools in this category return a number. GeoTopX returns the number and the whole path to it: the observed answer, the preserved artifact, the normalized observation, the metric and the recommendation. Every link stays reviewable, and the uncertainty appears next to the result instead of hiding behind a decimal place.