My use case is that I want to be classify documents into one of several categories, then depending on the category, extract certain fields from it. My question is for this kind of use case, what exactly is the difference between using AI Skills to do this versus using AI Doc Center? Looking around, I see some people saying AI Doc Center uses more tokens and that it can handle more complex cases, but I can't see anything in documentation about if that's actually true or not, and anything about when you'd want to use one or the other. I've been in loops reading the same page over and over again, so at this point I might have missed something, but if someone's able to help point me towards an answer, that would be most appreciated!
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Hi kl0001 ,Adding to what others mentioned.
AI Skills are more machine learning (ML) based, where you typically train the model by providing sample documents for each category you want to classify or extract.
AI Document Center (Doc Center) is more Generative AI (GenAI) based, where the model can classify and extract information from documents using prompts and configuration, with less reliance on traditional model training. It also provides capabilities for monitoring, testing, versioning, and deployment of document-processing models.
AI Skills generally do not consume GenAI tokens when using traditional ML-based classification and extraction models.
AI Document Center is token-based for its GenAI-powered classification and extraction capabilities, so token consumption and associated costs should be considered when designing large-scale document processing solutions.