Every agent has a named owner
Each agent acts under a clear identity, with a person who is accountable for what it does.
Governed agents
Agents with a job, an owner and clear limits.
Give every agent a role, tools, permissions, memory and approval rules, so it can do real work safely.
New to the idea? Read what makes an agent governed.
RA
Renewal analyst
Role, purpose, tools, memory, and escalation rules are explicit.
Skills Risk packet Vendor brief
Permissions Gmail readDrive scopedCRM update
Human approval above $50kNo external send without reviewer
Built for real work, inside clear limits.
Access only to what the job needs
Tools, systems and data are scoped to the role. Nothing is open by default.
Good workflows become reusable skills
When a process works, save it as a skill that approved agents can run the same way every time.
Create an agent with a role and scope
Set the purpose of the agent, the tools it may use, what it can remember and when it must stop for approval. Every rule is explicit and visible to the team.
- A role, an owner and a purpose
- Scoped tools and data access
- Approval rules built in from the start
Autonomy levels that grow with trust
Every agent starts with tight limits. At first a person reviews each piece of work before it goes out. As the agent proves itself on real work, you let it finish the clearly safe cases on its own and keep approval on everything sensitive. You can tighten the level again at any time.
- Start with draft and approve
- Open up routine cases as trust builds
- Sensitive actions keep their approval gates
- Draft only A person sends every result
- Approve each step The agent acts after a yes
- Approve risky steps Routine steps run on their own
- Run routine cases Sensitive actions still wait
Payments above threshold Always needs approval
Reusable skills
A skill captures an approved process step by step: collect the sources, apply the policy, draft the output, request approval and log the outcome. Agents in sales, finance, legal and support can reuse it.
Approved process Sales, finance, legal, and support agents can reuse it.
Collect sources
Apply policy
Draft output
Request approval
Log outcome
Model and policy rules
Choose which models an agent may use for which kind of work. Keep sensitive data on a private provider and send everyday drafts to a faster model.
- Bring your own LLM provider
- Model rules by type of work
- Policies applied across workflows
Low risk draft Fast model
Legal reasoning Approved advanced model
Sensitive data Private provider
Central policy
Controls cost, quality, latency, privacy, and task complexity.
How it works
From request to recorded result.
-
Pick a role
Describe the job the agent will do and who owns it.
-
Connect tools
Choose the apps and data sources it may use.
-
Set permissions
Scope what it can read and change in each system.
-
Add approval rules
Decide which actions pause for a person.
-
Put it to work
Assign requests and follow every run in the workspace.
Every feature runs inside the same six controls.
Identity, access, approvals, supervision, audit and policy apply to every agent and every run, whichever part of the workspace it happens in.
See governance and audit- Identity
- Access
- Approvals
- Supervision
- Audit
- Policy
FAQ
Governed agents: questions and answers
Short answers to what teams ask before they put this part of SoftworkerAI to work.
Contact us directlyWhat makes an agent governed?
A governed agent works inside limits you define. It has a named owner, scoped access to tools and data, approval rules for sensitive actions and a full record of what it did. You can pause or cancel any run at any time.
Do we need engineers to set up agents?
No. Agents are assembled from a goal, skills, tools and approval rules in a visual studio. During early access we also configure your first workflows alongside your team.
Can agents share skills?
Yes. A skill is a saved and approved process. Any agent with access to it can run it, so the same steps are followed across teams.
Which AI models can we use?
You can bring your preferred large language model provider and set model policies that decide which models handle which kinds of work.
Can we pause or stop an agent?
Yes. Any run can be paused, redirected or cancelled at any time, and the access of an agent can be changed or removed whenever you need.
The multiplayer workspace for humans and AI agents is how teams move beyond prompting and safely hand AI real work. It gives people one place to plan, approve, and oversee execution, so they can run work with AI agents they can govern and trust.