Trust & Security
Your Data, Your Technology, Your Decision
We plan security and human oversight around the actions an AI workflow is allowed to take. That means explicit data flows and hosting choices, role-based access, approval thresholds, exception handling and documented handover. The design follows your process, organizational responsibilities and infrastructure requirements.
What this means in practice
Human checkpoints are intentional
Documentation is part of delivery
An important boundary
Security claims must match the specific implementation.
Before implementation
Make the data and decision path explicit.
Data flow and location
Identity and access boundaries
Model and provider selection
Roles in the process
Give each person the view and authority their role requires.
- 01
Process participants
People doing the work see the inputs, tasks, decisions, and status they need to operate the process—without unnecessary access to financial, supervisory, or unrelated business data.
- 02
Approvers and managers
Approval authority can follow thresholds, responsibility, and escalation rules. Managers can see process flow, exceptions, bottlenecks, and performance while larger decisions reach the right level.
- 03
Finance and control
Finance, compliance, or control roles can review the commercial impact, relevant records, and required approvals without receiving broad operational access.
- 04
Process owners and administrators
Named owners can monitor workflow health, manage rules and role assignments, review changes, and keep the process aligned with organisational responsibilities over time.
In operation
Control the action, not only the model.
Approvals and thresholds
A workflow can draft, recommend, classify, route, or execute. The permitted action depends on confidence, policy, cost of error, and the person responsible for sign-off.
Exceptions and fallback
When the workflow is uncertain, a source is unavailable, or the case lies outside agreed rules, the system should surface the problem and route it to a human rather than improvising.
Logging and review
Logging must be useful for operation and proportionate to the data involved. The agreed review process should make it possible to inspect output quality, exceptions, and access without retaining unnecessary production data.
At handover
Leave you in clear, understandable control.
Documentation
Ownership and IP
NDA and confidentiality
Common questions
Answers before the call.
Can an automation run in our own environment?
Where the process and architecture support it, deployment in your own or another environment you control can be part of the design. The correct approach depends on your systems, data, security, operating capability, and required support model.
Do AI workflows always act autonomously?
No. Many useful workflows prepare, classify, retrieve, recommend, or route while a person retains the decision. Autonomy is a design decision, not a default.
What happens to access after a project?
Access responsibilities and removal are documented as part of handover. The exact process is agreed with your security and operating requirements.
AutoMates
Bring the constraint into the design conversation early.
Data residency, client hosting, approvals, access, and auditability are easier to solve when they are part of the problem definition, not an end-stage surprise.