One AI assistant. Three workflows.
A single AI handles returns triage, abuse detection, and evidence assembly — staying inside its boundaries with human approval on every high-risk decision.
What the AI does in each workflow
Returns Triage
Eligibility + routing
Inputs
- Order data (items, value, date)
- Customer history (return frequency, lifetime value)
- Channel metadata (Shopify, Amazon, eBay, Walmart)
Boundaries
- Operates within version-controlled rules
- Can't approve cases above risk threshold
- All scoring factors are visible and logged
Outputs
- Risk score with contributing factors
- Rule match (version + conditions met)
- Routing: auto-resolve or escalate
Human Review
- Cases above threshold go to human review queue
- Override requires actor ID + documented reason
Abuse Detection
Pattern detection + flagging
Inputs
- Cross-channel return patterns (frequency, timing, value)
- Customer behavior signals (serial returns, item swaps)
- Historical abuse indicators from resolved cases
Boundaries
- Flags patterns — doesn't deny or restrict customers
- Can't modify customer accounts or block transactions
- All flags include explanation and confidence level
Outputs
- Abuse risk classification (low / medium / high)
- Specific signals that triggered the flag
- Recommended action with rationale
Human Review
- High-risk flags require human review before action
- Rule changes based on patterns need admin approval
Evidence Assembly
Chargeback evidence + formatting
Inputs
- Order confirmation and invoice data
- Shipping proof and carrier tracking
- Customer correspondence (support tickets, emails)
Boundaries
- Can't submit evidence to processor without sign-off
- Can't modify original source documents
- Formats to processor specs (Stripe, Adyen, Visa TC40)
Outputs
- Processor-formatted evidence pack
- Completeness score with missing-item checklist
- Draft response narrative for reviewer
Human Review
- Evidence pack requires reviewer approval before submission
- Reviewer can edit, append, or reject any document
Four layers of control
Rules, approvals, transparency, and logging — from first action to final resolution.
Rules Engine
Every AI action is bounded by configurable, version-controlled rules. The assistant can't exceed its scope.
Approval Flows
High-risk actions need human approval. The AI surfaces recommendations — people make the call.
Explainable Signals
Every risk score and flag includes the specific signals behind it. No opaque decisions.
Activity Log
Every AI action, human override, and system event recorded with actor, timestamp, and reason. Fully exportable.
AI + human, in sequence
Ingest
New case arrives via API, webhook, or sync. The AI extracts structured data.
Evaluate
The AI computes risk score and matches to versioned rules. All factors logged.
Route
Low-risk cases auto-resolve. High-risk cases enter the human review queue.
Assemble
The AI drafts evidence packs, comms, and recommended actions.
Approve
Human reviewer evaluates the recommendation. Approve, reject, or escalate.
Record
Every decision, override, and outcome written to the activity log.
See how the AI handles your workflows.
Book a demo and we'll walk through AI setup, rules, and approval flows for your use cases.