aigw
Use case

Stop sensitive data reaching model providers

Every prompt your apps and agents send can carry a customer email, an API key, or a national ID straight to a model provider that may log or train on it. aigw inspects the traffic inline and acts on it before it leaves.

The problem

Prompts are unstructured, so sensitive data hides in them: a support ticket pasted into a summary, an AWS key in a stack trace, a national ID in a form. Once that reaches the provider you cannot take it back, and you often cannot even prove what left. Blanket-blocking AI is not an option, and asking every team to sanitize their own prompts does not scale.

How it works

Turn on the built-in rule packs, or write your own, and assign a policy to the traffic it should cover. A policy applies to all traffic or is scoped to a key, model, identity, tag, endpoint, tool, or agent, and each carries a mode.

  • Log only records a finding and forwards the request unchanged.
  • Redact replaces the value before it leaves.
  • Tokenize replaces it before it leaves and restores the original in the response, so the caller sees no change and the provider never sees the value.
  • Block refuses the request.
  • Exempt carves out a trusted key or service from a stricter policy.

Detection runs in the gateway, on the request and on the response.

What you get

  • Built-in packs for secrets and API keys, financial data, contact details, and government or national IDs, with per-country scoping.
  • Checksum validation on structured data (cards, IBANs, national IDs) to keep false positives low, plus your own terms and patterns as custom packs.
  • Response, tool-result, and agent-response scanning, so data cannot leak back out the other side.
  • Prompt-injection and jailbreak detection on the way in.
  • Findings recorded in the audit log as type and count only, never the raw value, so the evidence itself holds no sensitive data.

See governance for the full policy model.