Structured ticket triage
Extract order, issue, evidence, sentiment, language, urgency, and risk.
Open ↗AFTER-SALES TRIAGE AGENT
Classify, collect evidence, and propose—then leave the final decision to a person
Read return, damage, logistics, and warranty tickets; identify urgency, evidence gaps, and policy matches; draft a reply and recommendation for an agent to approve.
Try the interactive demoSEE THE WORK, NOT A CLAIM
Try a guided task with visible evidence and review.
Incomplete tickets, repeated policy checks, and multilingual delays consume service time, while refund and warranty decisions remain too risky for autonomous action.
Open interactive demo- Input
- The right earcup has no sound and I want a replacement. · 8
- Workflow
- Read ticket and order context → Classify urgency and risk → Check evidence and policy conditions
- Human boundary
- The agent cannot issue refunds, replacements, or warranty decisions; disputed, sensitive, and high-value cases require human final review.
WHO THIS FITS
A useful engagement starts with the right problem.
Growing support volume
Teams repeatedly classify return, logistics, damage, warranty, and parts requests.
Multilingual tickets
Description and response delays increase across markets.
Sensitive actions need governance
Refund, replacement, and warranty require policy, evidence, and authority.
THE CURRENT GAP
What has to change before technology creates value.
Missing evidence causes back-and-forth
Orders, photos, videos, serial numbers, and fault descriptions arrive incomplete.
Policy lives in memory
Similar cases receive different treatment depending on agent experience.
Automation boundaries are unclear
Letting a model decide creates financial, fraud, and customer risks.
DELIVERY PROCESS
A controlled path from evidence to a running system.
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01 / Read ticket and order context
Produces a visible, reviewable state before the next step.
Input · evidence · state -
02 / Classify urgency and risk
Produces a visible, reviewable state before the next step.
Input · evidence · state -
03 / Check evidence and policy conditions
Produces a visible, reviewable state before the next step.
Input · evidence · state -
04 / Draft a reply and proposed resolution
Produces a visible, reviewable state before the next step.
Input · evidence · state -
05 / Approve, edit, or reject as a human reviewer
Produces a visible, reviewable state before the next step.
Input · evidence · state
ACCEPTANCE
Define success before expanding scope.
Reliable category and risk
Check issue type, urgency, and escalation on anonymized historical tickets.
Complete evidence request
Each issue asks for the right order and proof fields.
Clear human responsibility
High-risk recommendations show evidence and record final approval.
BOUNDARIES
What this engagement does and does not promise.
No automatic refund or replacement
Money, inventory, and warranty actions need human approval.
No unverified identity
Order and customer data require login or secure verification.
Disputes and safety issues escalate
Personal safety, fraud, legal threats, and major complaints bypass automation.
FAQ
Questions teams ask before starting.
Can replies be sent automatically?
Low-risk acknowledgements can be evaluated later; the demo and pilot produce drafts only.
Can it query Shopify orders?
Yes with customer verification, minimum scopes, and protected-data controls.
How is human review recorded?
The workspace stores the proposal, evidence, edits, approver, time, and final action.
