AI Doc Center vs AI Skills

Certified Senior Developer

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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    Certified Lead Developer

    AI Skills are the runtime objects. You build them directly pick classification or extraction, train or prompt them, and call them from a process via smart services like Classify Document and Extract from Document.

    Doc Center is not a separate engine. It's an application that generates and maintains those same AI skill objects and their process models for you, then layers on versioning, reconciliation, accuracy metrics, token monitoring, and deployment.

    Both end up as AI skill objects at runtime. The choice is whether you build and manage the AI skill yourself, or let Doc Center generate it and give you versioning and accuracy metrics. Doc Center's models are gen-AI backed (tokens, better on varied layouts); an AI skill you build directly can be trained ML: no tokens, but needs consistent layouts and retraining.

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  • 0
    Certified Lead Developer

    AI Skills are the runtime objects. You build them directly pick classification or extraction, train or prompt them, and call them from a process via smart services like Classify Document and Extract from Document.

    Doc Center is not a separate engine. It's an application that generates and maintains those same AI skill objects and their process models for you, then layers on versioning, reconciliation, accuracy metrics, token monitoring, and deployment.

    Both end up as AI skill objects at runtime. The choice is whether you build and manage the AI skill yourself, or let Doc Center generate it and give you versioning and accuracy metrics. Doc Center's models are gen-AI backed (tokens, better on varied layouts); an AI skill you build directly can be trained ML: no tokens, but needs consistent layouts and retraining.

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