Management: Enforcing New Policies Company-Wide
These use cases make the Find and stop AI compliance risks and Local AI Operation for Sovereign Enterprise Operations solutions concrete. The scenarios are illustrative and show how DAOS works day to day.
At a glance
The problem
Technical change and new regulatory requirements demand ongoing adjustments to AI policies. Without central enforcement, it stays unclear whether a new rule has actually reached everyone – or only exists on paper.
The customer
IT or compliance lead
Manages the company's AI policies and has to enforce new requirements reliably.
The system
DAOS Policy Engine
Central management of every policy, including versioning, rollout, and logging.
The goal
Enforce new policies company-wide without friction
Every change lands reliably, without employees having to change anything themselves.
The result
A new policy is active across the whole fleet within minutes, with a log of where it succeeded and where it didn't.
The path at a glance
Policies at a glance
New policy created
Targets selected
Rollout started
Log & status
Illustrative path – the detailed walkthrough is below.
The journey from the customer's side
- 1
Policies at a glance
A list shows every active policy and its scope – system, user, or local level. The lead sees instantly what applies right now, without digging through individual config files.
- 2
Create a new policy
An existing policy can be duplicated or built from scratch – directly in JSON, in the overview, or in a dialogue with an AI agent that suggests changes.
- 3
Select target machines
A list of all machines with name and hardware shows who gets the update. Individual devices or whole user groups can be checked off.
- 4
Rollout at the push of a button
The new policy goes out to every selected target in one click – nobody has to touch machines individually.
- 5
A log instead of a guess
The local Policy Engine checks on every machine whether the settings can actually be applied, and logs success or failure along with a suggested fix. Employees are informed of the new rule but don't have to change anything themselves.
Further scenarios
Staged rollout
A new policy can go out to a small test group first, before it goes active company-wide – problems surface in a small circle, not across the whole fleet.
Roll back on failure
If a rollout fails on a relevant number of machines, the previous policy version can be restored in a targeted way.