# Earn every permission.

> Aumenza's design commitments for identity, approval, evaluation, audit, data boundaries, and recovery.

Canonical: https://aumenza.ai/trust · Last updated: 2026-08-21

Trust / Authority and recovery

AI becomes operational when people can see what it did, understand why, constrain what it may do next, and recover when it is wrong.

Part of the delivery design

Identity, approval, audit, and rollback are sized to the workflow and verified during delivery.

## Safety lives inside the workflow.

Control principles

Governance is implemented in identities, permissions, interfaces, evidence, and operating procedures.

Authority expands in stages: read-only observation, recommendation, human-approved action, then bounded automation only when the evidence and risk support it.

### Identity before autonomy

Every production tool call must have an authenticated identity, a least-privilege permission boundary, and an accountable owner.

### Shadow before write

Historical replay and parallel runs establish behavior before production actions are considered.

### Evidence before confidence

The system must expose sources, limits, and escalation paths; important decisions are evaluated on real task examples.

### Humans at the control point

Consequential workflows need explicit paths to approve, reject, correct, pause, and take over.

### Rollback is a feature

Versions, fallbacks, kill switches, and the original human process must remain available in proportion to risk.

### Data stays in context

Our intended default keeps customer data in its owning environment or required region; reusable methods may move under agreement, raw data does not by default.

These are delivery requirements, not a claim of external certification or pre-approved access in a customer environment. Exact controls and evidence are agreed for each workflow before authority expands.

## Work should leave evidence.

The operating record

What is recorded depends on risk and customer policy, but the design goal is a reviewable chain from task to action and recovery.

- Task and model version
- Authorized context and sources
- Policy and permission decision
- Human approval, rejection, or correction
- Action result, error, and recovery path

[Inspect the evidence boundary](https://aumenza.ai/demonstration#workbench)

## Reusable methods move. Raw customer data does not by default.

Data boundaries

Deployment architecture is chosen with the customer. Data stays in its owning environment or required region unless a documented, authorized path says otherwise.