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What bazqux2 said is accurate. I'll go further to say that the kinds of work Palantir is involved in is mostly probabilistic. Especially intelligence work. So, use of models requiring certainty or straight logic in areas rife with uncertainty & degrees of truth seems set up to fail outside easy inferences. One can encode the logical stuff in probability models but harder to do reverse. Hence, their underlying tech should be probabilistic, fuzzy logic, or something similar for best results instead of just some results.

Far as ontologies in general, they have a mixed, track record. They take a lot of work to create. Then, they have to be mapped to real world inputs and outputs. One way they got applied is so called business rules engines or business process management. It's like a subset of ontology approaches of past. Here's a company that uses the real thing for enterprise software with Mercury language for execution part:


Also, Franz Inc, of Allegro Common LISP, covers many of the same use cases as Palantir with their ontological tooling.


So, there's definitely companies using it for long periods of time for real-world, use cases. Palantir just seemed to be mixing it with hype and secrecy to maximize their sale price later. ;)

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