A deep dive into the proxy-first architecture that powers our vendor-agnostic AI risk control plane.
Every AI request passes through the AixSafe proxy, which enforces policy and logs telemetry before reaching any external provider. The loop is synchronous — your application waits for AixSafe to approve, scrub, and forward the request.
Prompt from any app, agent, or Copilot integration is routed to the AixSafe proxy endpoint instead of the LLM vendor directly.
The policy engine inspects the prompt for PII, tokens, secrets, and policy violations. Detected violations are blocked or masked before forwarding.
Sanitized, policy-approved prompt is forwarded to the cloud LLM (OpenAI, Anthropic, Gemini, etc.) via a secure outbound connection.
The completion is inspected for sensitive output. Both prompt and response are hashed and appended to the immutable audit vault.
The verified, safe response is returned to the calling application with telemetry metadata attached in the response headers.
Every packet is analyzed for PII, API keys, and sensitive local data before it ever hits the public internet.
Apply RBAC and quotas to LLM usage. Ensure only authorized personnel can access high-cost or sensitive model endpoints.
Sensitive data is automatically masked or hashed in the prompt before reaching the vendor, ensuring zero-knowledge privacy.
Completion payloads are logged and hashed, providing an immutable audit trail for legal and compliance reviews.
Book a technical demo to see how the proxy handles real-world PII masking and agentic control.
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