Inova reports an evaluation of models with predefined responses and a comparison with specialized classifiers. For classification integration, the lesson is to define the task and what makes an outcome acceptable before choosing a model.
Write down categories, examples and routing rules first. Reserve an evaluation sample and inspect errors by category, including ambiguous cases. A well-formed output can still be incorrect; format and performance need separate criteria.
Minimize the input. If a category depends on a message's subject, a name or phone number may add no value. Apply the personal data policy before inference and compare whether processing changes classification or removes information necessary for the task.
Keep human review where an incorrect decision has significant impact. Rota offers processing and model integration in the supported workflow; it does not provide the specific classifiers cited in the news or guarantee clinical suitability, class accuracy or complete text anonymization.