Can we honor a right-to-erasure request across AI artifacts?

Erasure is simple in a database and hard in an AI stack, because personal data propagates into embeddings, cached answers, conversation histories and logs. Deleting a source document while leaving its embedding in the index has not honored the request: the content remains semantically retrievable.

Because Centralpoint indexes at the record level and the index sits in the organization's own environment, the derivatives of a record can be enumerated rather than guessed at. Removing the record removes its basis for retrieval, and governed cached answers derived from it are invalidated on the same lifecycle instead of persisting as independent artefacts.