First agent deployments
Build the operating habits, approval model, and evidence plan that later agents can learn from.
Risk-based implementation
Secure AI agent deployment, one bounded use case at a time.
Move from a promising idea to a controlled agent pilot with least-privilege access, approved tools, human approval points, monitor-only logging, realistic tests, and a documented rollback and shutdown plan.
One use case
Approved tools
Controlled tests
Rollback ready
Who It Is For
For Maine teams ready to implement—but not ready to hand over unlimited authority.
Designed for Portland and statewide organizations with a defined workflow, an accountable owner, and the willingness to test assumptions before production use.
High-value internal workflows
Bound document, research, intake, coding, or operations support to approved data, tools, users, and outputs.
Existing prototypes
Replace broad developer access and informal testing with named ownership, scoped credentials, test cases, and stop criteria.
Deployment Risks
Design the boundary before connecting the tools.
Overbroad access
The agent can read or change more files, applications, records, or environments than the use case requires.
Unsafe tool combinations
Individually reasonable tools create a higher-risk path when the agent can chain them without a review gate.
Production-first testing
Real customers, live data, or consequential systems become the test environment before failure modes are understood.
Hidden credential scope
The workflow inherits a user session, administrator key, or service account that exceeds the agent’s role.
Approval fatigue
Review points are so frequent or unclear that people approve reflexively, undermining the intended control.
No safe exit
The team lacks stop criteria, rollback steps, access revocation, queued-work handling, or a restart decision owner.
Secure Agent Pilot
- One bounded business use case and named accountable owner
- Data classification and approved input/output boundary
- Least-privilege identity, credential, file, tool, application, and destination plan
- Approved-tool list and prohibited-action list
- Human approval matrix for consequential steps
- Monitor-only logging and evidence-retention plan
- Controlled test suite covering expected work, misuse, failure, and recovery
- Go, pause, stop, rollback, shutdown, and restart criteria
- Pilot handoff documentation and owner briefing
Implementation
How the secure pilot works.
Choose and bound the use case
Define the users, business outcome, data, tools, systems, autonomy level, prohibited actions, and measurable success and stop criteria.
Configure least privilege
Create or select the narrowest practical identities, credentials, files, tools, destinations, and time limits for the task.
Test with controlled evidence
Use non-sensitive or minimized data first, exercise normal and adverse cases, verify approvals, and confirm logging without enabling enforcement by assumption.
Run, review, and decide
Operate within the agreed pilot boundary, review evidence, correct gaps, test shutdown, and make a documented human decision about the next phase.
Human Approval & Least Privilege
Autonomy should match consequence.
Low-risk, reversible steps can be tested with bounded autonomy. Sensitive sends, financial actions, access changes, deletions, code deployments, customer-impacting updates, and other consequential work return to an identified person with enough context to make a real decision.
Common Questions
Secure deployment FAQ
What makes an AI agent pilot bounded?
A bounded pilot has one approved use case, named users and owners, limited data and tools, scoped credentials, defined approval points, a time window, success and stop criteria, and a tested shutdown path.
Will the agent act without human approval?
Low-risk steps may be automated within the approved boundary, but consequential messages, transactions, access changes, code changes, record updates, or other sensitive actions remain subject to named human approval.
Do you support every agent platform?
No. Platform fit is evaluated during scoping. Implementation depends on documented permission controls, available logs, deployment options, integrations, and the ability to test and stop the workflow safely.
Deploy the smallest useful agent before scaling the system.
Bring one workflow, one accountable owner, and the access questions you need to resolve.