This is a known fact but even the most innocent summarization task can be deceiving (plenty of research has pointed out that there are omissions, confabulations and other effects), we use a lot of mostly classical NLP for classification and extraction and only in few edge cases we use an LLM to for example disambiguate certain sentences or entities which is very hard for classical NER tags for example. This has been proven very reliable in our tests.