
Langdock wraps ChatGPT, Claude, and Gemini in a compliant contract.
Privatemode removes plaintext access underneath, not just on paper.

Privatemode encrypts prompts and responses end-to-end and processes them only inside hardware-isolated confidential-computing environments. Even Privatemode can't see the plaintext. Langdock adds a GDPR-compliant contract on top, but requests are still routed to OpenAI, Anthropic, or Mistral and processed in plaintext there.

Privatemode is one layer, hardware-enforced end to end. There's no gateway operator, no model provider, and Privatemode itself can't see your data. With Langdock, every request passes through its gateway operator in addition to the underlying model provider, adding a party with theoretical access instead of removing one.

With Privatemode, you cryptographically confirm what's running before you send any data. That's proof, not a policy page. Langdock offers no technical mechanism to verify its privacy claim. You're relying on the DPA and its word alone.

Privatemode is available today as a web app, desktop app, and OpenAI-compatible API, no procurement cycle in between. Rolling out Langdock is also reasonably fast. Setup time isn't the argument for switching here, data access is.
Langdock wraps ChatGPT, Claude, and Gemini in a compliant contract, but the underlying provider still sees your data unencrypted. Privatemode removes that access entirely, hardware-enforced.
One layer, hardware-enforced end to end. No gateway operator, no model provider, and not even Privatemode can see your data.
A GDPR-compliant gateway in front of OpenAI, Anthropic, or Mistral. Prompts still reach the underlying model provider unencrypted.
We're happy to show you around and give an overview of what's possible.
Privatemode vs. Langdock
Gateways like Langdock give you a single, GDPR-compliant interface to multiple AI providers. The underlying model (OpenAI, Anthropic, Mistral) still processes your prompts in plaintext on its own infrastructure. Privatemode removes plaintext access at every step, using hardware-enforced confidential computing.
Trusted by security-critical teams at enterprises and public institutions
