Handing work to an agent raises a fair question: if it can act across my business, what stops it doing something it should not? The answer is that a well-built agentic system is more constrained than a person with a login, not less, because the limits are enforced by the software at every step.
Permission-aware by design
An agent acts on behalf of a person, and it inherits exactly that person's permissions, no more. The check happens twice: when the tools are offered to the agent, so it is never even shown an action it may not take, and again when an action runs, so nothing slips through. Access fails closed, which means anything not explicitly allowed is denied rather than waved through.
Isolation between businesses
Every business has its own data, kept separate from every other. Where an operator runs a branded network, each network gets its own database and storage, so customer data is never pooled or shared across networks. An agent working in one workspace has no path to another.
Encryption and your data rights
Data is encrypted in transit and at rest. It is yours: it is not used to train models, and you can ask to access, correct, export, or delete it. Those requests go through a clear process, and where a branded operator is the controller of your data, the request goes to them with the platform helping them fulfil it.
An audit trail you can read
Because the agent works through defined tools rather than poking at a database, every action it takes is recorded: what was done, on whose behalf, and when. That turns "the AI did something" into a reviewable log, which is what accountability actually requires.
The questions worth asking
Of any agentic software, ask: does the agent inherit the acting person's permissions, and are they enforced when tools run? Is my data isolated per business and encrypted? Is it kept out of model training and exportable on request? Is there an audit trail? SOIS answers yes to each; the security page has the detail.