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pros

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Use AI without compromising data security or privacy

privatemode.ai
1 分·作者 pros·27天前·0 评论

Run Claude Cowork against your own cloud inference provider

claude.com
2 分·作者 pros·2个月前·0 评论

BSI (Germany) defines when a cloud is sovereign

heise.de
3 分·作者 pros·3个月前·0 评论

[untitled]

22 分·作者 pros·4个月前·0 评论

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pros
·3个月前·讨论
[dead]
pros
·3个月前·讨论
You cannot — not with the model alone. It gives you spans + types, not identity.

You need to do that part yourself after the model runs. The filter gives you spans; for each one, assign a stable ID (PERSON_1, PERSON_2) and keep {PERSON_1: "Harry", PERSON_2: "Ron"} next to the document. Swap IDs in before the LLM call, swap originals back in the reply.

Scoping that map to a document/project keeps the same person consistent across calls, so Harry stays PERSON_1 instead of becoming PERSON_3 the next time he's mentioned.

(Disclosure: I'm building a Mac privacy tool, RedMatiq, that does exactly this. The mapping layer turned out substantially harder than detection.)
pros
·3个月前·讨论
I'm using GLM 5.1 for the last two weeks as a cheaper alternative to Sonnet, and it's great - probably somewhere between Sonnet and Opus. It's pretty slow though.