ChatGPT is built for breadth and convenience. Tresor is built for confidential work where provider-visible processing, key ownership, and auditability actually matter.
Works well when
Versatile and broad
It handles a wide range of everyday prompts, drafting tasks, and exploratory questions without much setup.
Ecosystem and integrations
Teams can extend it with a large surrounding ecosystem of tools, plugins, and connected services.
Becomes the better fit when
Confidential by design
Zero-access architecture keeps prompts, files, and outputs readable only inside sealed execution instead of a provider-visible app stack.
EU-sovereign runtime
Inference and storage stay in European secure enclaves, which gives legal, procurement, and security teams a far cleaner operating story.
The decision usually comes down to who can read the data, who owns the keys, and how much proof your team needs when the workflow is reviewed.
If the work is not sensitive, ChatGPT wins on familiarity, breadth, and the speed of just opening a tab and getting started.
It handles a wide range of everyday prompts, drafting tasks, and exploratory questions without much setup.
Teams can extend it with a large surrounding ecosystem of tools, plugins, and connected services.
It is strong for ideation, writing support, code generation, and fast interactive problem solving.
Once prompts, files, or outputs become sensitive, the question stops being which assistant is more capable and becomes who can read the plaintext and how you prove the answer.
Zero-access architecture keeps prompts, files, and outputs readable only inside sealed execution instead of a provider-visible app stack.
Inference and storage stay in European secure enclaves, which gives legal, procurement, and security teams a far cleaner operating story.
Audit logs, policy boundaries, and verifiable processing make GDPR and HIPAA mapping operational instead of aspirational.
You stay in control of key ownership, retention decisions, and access posture end to end.
Many teams will use both. The split is usually simple: public tasks in a public assistant, confidential tasks in a runtime built to keep operators out.
You want breadth, speed, and convenience for non-sensitive creative, coding, and productivity work.
You work with regulated or confidential data and need sovereignty, compliance, and key ownership as part of the product.
