Quick overview
This workflow provides a public hosted chat that routes messages through the Saklam Bridge to mask PII on-premises before calling models like Claude, GPT, or Mistral, then restores the original values in the response.
How it works
- Exposes a public hosted chat interface and receives each user message.
- Sends the message to an AI agent that uses an OpenAI-compatible chat model endpoint.
- Routes the model request through the self-hosted Saklam Bridge, which masks PII locally before forwarding the prompt to your chosen LLM provider.
- Receives the provider’s response back through Saklam Bridge, which unmasks the placeholders to restore the original PII.
- Returns the final unmasked answer to the hosted chat user.
Setup
- Deploy the Saklam Bridge container in the same network as n8n and configure it with your Saklam license and your LLM provider API key.
- Create an OpenAI API credential in n8n that points its Base URL to your Saklam Bridge endpoint (for example,
http://saklam-bridge:4000/v1) and uses the Bridge master key as the API key.
- Select that OpenAI credential in the chat model node and set the model name to the provider model you want to use (for example,
claude-haiku-4-5, gpt-4o, or mistral/mistral-large-latest).
- Enable the hosted chat trigger and test a message while checking Saklam Bridge logs to confirm only masked text leaves your network.
Requirements
- Self-hosted n8n (Docker)
- Saklam Bridge container — commercial, 7-day free trial (setup guide: https://saklam.com/en/docs/n8n)
- A pay-as-you-go API key for your LLM provider (bring your own key)
Customization
- Point the model node of any existing workflow (email automation, extraction, classification) at the same Bridge credential — that workflow is masked too. Switch providers by model name (claude-, gpt-, mistral/*), no workflow changes needed.
Additional info
Verify what actually left your network at any time with: docker logs saklam-bridge. Full documentation: https://saklam.com/en/docs/n8n