Security and governance
Control, permissions and traceability
How access, approvals and data are managed when part of the work is delegated to digital collaborators.
Governing a digital workforce.
A digital collaborator has access to company information and takes action. It needs to be managed with the same rigour applied to managing people's permissions.
Identity and roles
Every agent has an identity, an operating scope and a verifiable set of permissions.
Principle of least privilege
Access limited to only the sources needed for the assigned task.
Full traceability
Actions are logged and reconstructable, including delegations between agents.
Human in the loop
Steps with external or financial impact require explicit approval.
Environment separation
Testing, prototyping and production stay distinct, with separate data and permissions.
Data handling
Clear policies on what is retained, for how long, and where.
On-premise deployment
Genesis can be installed inside the company's infrastructure, with isolation between tenants and environments.
Credentials and tools
Encrypted secrets, per-agent capabilities and protections on outbound calls.
These are architectural features of the product. 93labs does not claim certifications or compliance that have not been independently verified.
Autonomy with a handbrake always within reach.
Delegating work to AI only makes sense if it stays clear who can do what, with which data, and with what ability to step in.
Per-agent permissions
Each digital collaborator only accesses the sources, inboxes and tools you've assigned to it.
Human approval
You define which steps require confirmation before they're executed or sent externally.
Verifiable history
Every action logs its input, sources consulted, outcome and time of execution.
Process rules
Exceptions and operating limits are defined by the company, not left to the model.
Data boundaries
You decide which information can reach an external service and which stays internal.
Instant interruption
Any agent can be suspended or restricted at any time, without stopping the others.
Control isn't an add-on feature: it's the precondition for using AI on real processes.
Your data stays where you decide.
For many companies the constraint isn't cost, it's confidentiality. That's why execution can take place inside your own infrastructure.
Local execution
Models run on company servers or dedicated hardware, with no content sent externally.
Hybrid mode
Sensitive tasks run locally, cloud capacity is used only where extra processing power is needed.
Control over data destination
You define which tasks must stay within your infrastructure and which can use external services, according to your organization's policies.
Defined perimeter
You know exactly which flows stay internal and which can leave, for every single task.
Designed for companies handling industrial, contractual or personal data.
What's the first task you'd delegate?
Tell us how you work today. Together we'll assess whether there's a digital collaborator that would deliver a real, measurable and sustainable benefit.