Has AI policy on paper and wants to enforce it in practice now — not hope employees read it.
Compliance · Guardrails
Turn your AI policy into guardrails the control plane enforces deterministically. Numaga ships the defaults; you turn them on, off or tune them for your organisation.
Has AI policy on paper and wants to enforce it in practice now — not hope employees read it.
Wants sensitive data and risky content caught at the gate, not discovered after the fact.
Wants to see when personal data would be shared — and have it masked or blocked automatically.
The problem
You have written AI policy: which data may go to a model, what may not, which use is prohibited. But a policy document stops no one. Without enforcement, you only learn something went wrong once it already has — if you find out at all.
Guardrails turn that policy into behaviour on the control plane. Personal data, forbidden keywords, harmful content — caught before the model call. And every violation that would otherwise have gone unseen now sits in your audit trail.
How it works
Guardrails are ready; you decide which are on and how strict.
The control plane recognises PII in every prompt. Per organisation you choose what happens — block, or mask automatically before the model — so GDPR-sensitive data never leaves the boundary unchecked.
Define which terms may not reach a model — project names, trade secrets, client names. The guardrail catches them at the gate.
Numaga defaults for self-harm and NSFW content are ready. Turn them on for your whole organisation or tune them per group.
Every guardrail runs deterministically on the control plane, before each model call — and every hit sits in the immutable audit trail. Violations that would otherwise stay invisible now surface.
We show how to enforce your policy as guardrails on the control plane.
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