Hi all,
I am somehow confused with all these different intelligent services that partially do the same and partially built on top of each other.
So if I understand correctly, Smart Classifier and Smart Metadata are cloud-based services with a essence of knowledge graph and I assume some AI learning capabilities.
On the other side, there is Discovery and Information Extractor (Text Analytics and Matcher). My understanding of Discovery service is that it enforce classification of documents and properties based on configuration and rules and that not really work with concept of suggestions. Also it needs Smart Classifier for categorization (which means 2 licences) and is dependent to cloud service as well.
Information Extractor seems to be the only service which works on-premise without need of cloud services. Is my understanding so far right?
I am wondering if Information Extractor services can be used with documents coming through connectors to suggest users class and properties during promotion process. Could they be configured in a way when people bring documents from "outside" and just drop them to M-Files that these services suggest class and properties for dropped document? Somehow all documentation explains cases that these services run periodically in backend and need their time for processing. It is not clear if they would support such on-demand cases. Of course, if possible, this would help users a lot not to always need to provide all metadata by themselves.
Thanks for thoughts and clarifications.
Dejan
