aigw
Use case

Produce the evidence auditors ask for

When an auditor asks how you govern AI, "we trust our developers" is not an answer. aigw records what happened on every call and keeps it in a trail you can show.

The problem

The EU AI Act, GDPR, NIS2, and ISO 27001 all expect the same underlying thing: you can say what AI you run, who used it, what data went through it, and what controls applied. If your AI calls go straight to a provider, none of that exists, and assembling it after the fact is a project.

How it works

Because every call passes through aigw, every call leaves a record: the identity behind it, the model, the policy outcome, the cost, and the data categories it touched. The audit trail is checkpointed so tampering shows. Content retention is opt-in and redacted on ingest, so you can keep evidence without keeping the sensitive data inside it.

What you get

  • A per-call governance record: who, which model, which policy, allowed or blocked, and what was detected.
  • A tamper-evident audit trail you can export for a review.
  • Governed content logging, off by default, redacted when on, with its own retention window.
  • A live inventory of the models in use and the traffic against them, so an AI register is a report rather than a spreadsheet.

This supports your AI Act, GDPR, NIS2, and ISO 27001 evidence; it does not replace your own assessment. See governance.