AI Operations Agents
Run recurring internal workflows against your written policy: check requests for completeness, prepare approvals for a decision-maker, and compile reports from systems your team already uses.
The Problem
- • Approvals stall waiting on missing information
- • Policy is applied differently by team and reviewer
- • Recurring reports are rebuilt by hand each cycle
- • Requests are tracked across chat, email, and tickets
- • There is no clear record of who approved what, and why
The Solution
- ✓ Check each request against your documented policy
- ✓ Collect missing fields before routing for approval
- ✓ Prepare an approval summary with the supporting data
- ✓ Escalate exceptions and threshold breaches to an owner
- ✓ Keep an audit trail of inputs, rules applied, and outcome
Pilot Metrics
Capture a baseline first, then compare the pilot against the same request types, approval thresholds, and policy standard.
Quality
Policy compliance and approval decision accuracy
Speed
Cycle time from request submitted to decision
Operations
Exception rate, rework, and cost per request
Suggested Pilot Scope
- • One workflow with a single named process owner
- • Requests below an agreed value or risk threshold
- • Recommend-only mode before any automated approval
- • Named approvers and a documented exception path
Inputs We Need
- • Sample requests with confidential details removed
- • The written policy, thresholds, and approval matrix
- • Decisions that must always stay with a person
- • Baseline cycle-time, exception, and volume measures