At their essence, knowledge graphs (like metaweb) are based on semantic relationships, e.g. coffee is a beverage, apple and banana are fruit, diabetes is a disease, etc. System, instead, is based on statistical relationships (collected and synthesized from data, models, and papers): A predicts B, C is caused by D, E and F are highly correlated, G and H change together, etc. While statistics (probabilities for example) can definitely be used in a KG (and certainly in large scale ones), the nature of the relationships themselves (x is a movie, x stars y) are semantic.
By organizing these (billions and billions of) statistical relationships on System, anyone will be able see anything that's important to them as the system it truly is, rather than the silo we often see today.
We hope these will be complementary ways of understanding the world -- one based on language, the other based on statistics. Importantly, System leverages the same core ontology as Wikipedia (i.e. Wikidata) so the definition of "coffee" on System is the same as on Wikipedia. So these two ways are very intentionally interoperable.
You can read more about System's methodologies in our technical documentation: docs.system.com/system.