Application: Safe Everyday AI Use for Every Employee
These use cases make the Worry-Free, Local Operation of AI Agents solution concrete. The scenarios are illustrative and show how DAOS works day to day.
At a glance
The problem
Employees often don't know which data they're allowed to feed into an AI and which policies apply – the uncertainty either slows adoption or leads to violations nobody intended.
The customer
Employee in day-to-day work
Uses AI tools and agents productively without being a compliance expert.
The system
DAOS chat assistant
Checks in the background which data and models are allowed for a given request.
The goal
Work without having to think about the rules
A response only appears when a limit is actually reached.
The result
The check runs automatically alongside every request. Employees keep working productively and only get a response when a limit is actually reached.
The path at a glance
Request made
Sources selected
Model chosen automatically
Answer with a note
Illustrative path – the detailed walkthrough is below.
The journey from the customer's side
- 1
A request like any other
The employee writes their request like in any chat – without first checking which model or which rule is in charge right now.
- 2
Add sources
Files or company connectors can be added to the request. Every source already carries its own security clearance – the employee doesn't have to judge it themselves.
- 3
The right model in the background
The system checks which combination of data and model is allowed, and automatically picks the matching provider – local or cloud-based.
- 4
An answer with context
The employee gets their answer along with a note on which model was used and – if it was processed locally – that this is why it will take a little longer.
Further scenarios
A warning instead of a block
If the system detects a critical combination, the employee gets an understandable warning instead of a silent rejection – including a suggested, allowed alternative.
A traceable history
Every request stays documented, including the model chosen and the sources used – without the employee having to log anything themselves.