Use cases / Finance and operations
Autonomous Workflows
Embed AI in how the organization operates, step by governed step.
01
Problem
Processes span systems and teams, and scripts break at the first exception. Fully autonomous AI with no limits is not acceptable to risk owners.
02
AI capability
Orchestrate multi-step processes across systems, handle exceptions with reasoning, and pause for people where policy says so.
03
Data
The agent works from the context you connect, not from the open internet by default.
- Process definitions
- Systems of record via connectors
- Policies and thresholds
- Run history
04
Agent
Workflow Agent
Executes defined processes and escalates exceptions at the points the policy marks.
05
Workflow
- 1. Trigger
- 2. Run step
- 3. Policy check per step
- 4. Approval gate where required
- 5. Handle exception
- 6. Complete
- 7. Monitor and review
06
Governance
Governance runs inside the agent at runtime: policy changes what it can actually do.
Can
- Run steps it is assigned
- Call approved connectors
- Retry and branch on exceptions
- Pause for approval
Cannot
- Add steps or tools to itself
- Skip an approval gate
- Act outside its data classification
- Change its own policy
Requires approval
- Steps marked as gates
- Irreversible actions above threshold
- New connectors
Records
Agent identity, Data accessed, Model used, Output, Tools called, Policy applied, Decision, Approval, Action, Outcome.
Suggested starting autonomy: L3 Supervise
L3 lets a workflow act within limits under monitoring. Start new workflows at L2 and raise per step with evidence.
07
Outcome
What you measure, so the agent earns more autonomy on evidence:
- Process cycle time
- Share of runs completed without escalation
- Gate decisions on record
- Policy blocks and their reasons
Questions
Can a workflow run with no human involvement?
Where policy allows. Autonomy is set per step, and higher levels operate within strict policy and risk bounds.
What happens when something unexpected occurs?
The step escalates according to policy and the run is recorded.
Build it on the platform
Related use cases
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- AI CodingFaster engineering without giving agents the keys to production.