From individual hands to the organisation.
We move AI from something individuals use to something the company uses: the company decides what may be used and where, every use is recorded, and the scope widens as each area is verified. iOOz develops OO, an AI adoption platform for companies, and N3, a customer-management AI for customer-facing venues.
What must be governed is shifting from text to action
Prohibition is not a solution
A blanket ban is the easiest control and the most expensive one. Teams move to personal devices and personal accounts, and the usage does not stop — it only becomes invisible.
Visibility alone is not enough
Once you can see what is being used, the next question is how far you are willing to allow it. Without an articulated basis for that decision, the logs are collected and never acted upon.
Agents act on their own
Earlier systems presented information. Agents execute. When failure translates directly into damage, you need conditions before execution and evidence after it.
Not blocking — allowing, with conditions attached
What enterprises actually need is not the ability to stop something. It is the ability to resume safely once it has been stopped. iOOz is built around granting execution with a defined scope, purpose, and expiry, rather than a binary allow or deny.
- 01DiscoverIdentify which AI usage requires managed authority
- 02DecideApply baseline rules to allow or hold
- 03GrantPermit execution within a defined scope and expiry
- 04RecordKeep who executed what, why, and under which conditions
- 05RevokeSuspend or expire authority as circumstances change
Two businesses
Enterprise AI execution control
An operational layer covering visibility, conditional execution rights, and audit trails. Phase 0 — visibility — is currently in development.
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Customer-management AI for in-person service businesses
A sales operations tool for venues in the night-time economy, recording and managing customer follow-up. In operation since 2026.
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Selective freedom and ego-based symbiosis
Once AI absorbs the labour required to survive and the labour required to earn, what remains for people is the activity of living well together. That requires a structure in which people holding different values can coexist without abandoning them. Enterprise AI governance is the first implementation of that idea.
Read the vision→