Service 01 · Support
AI support triage.
Deflect the repeatable. Escalate the rest. I build support triage that classifies the ticket, retrieves the right answer, drafts a response, and hands edge cases to a human with full context.
- Best for
- Commerce & marketplaces
- Pilot
- 4–6 weeks
- Approach
- Evals before launch
- Review
- Human on edge cases
The problem
Support queues grow faster than headcount. A generic chatbot answers confidently and wrongly. A prompt demo looks good in a meeting, then fails on real tickets, real order data, and real refund policies.
The missing work is not the model. It is the workflow around it: retrieval, confidence thresholds, escalation rules, evaluation, and a cost ceiling.
What I build
Ticket classification
Intent, urgency, order or account context, and the right queue.
Retrieval
Answers grounded in your help centre, policies, and order data.
Draft + confidence
A reply with sources and a threshold; low confidence escalates.
Escalation policy
Refunds, legal, vulnerable customers, and anything irreversible.
Eval set
150–300 labelled real tickets with failure budgets and regression checks.
Cost dashboard
Cost per resolved ticket, latency, escalation rate, deflection rate.
How it runs
-
01
Audit
1–2 weeks
Ticket volume, top intents, current tooling, data access, and a cost baseline.
-
02
Eval set
1 week
Sample real tickets, label expected outcomes, and agree on a failure budget.
-
03
Pilot
3–4 weeks
Retrieval, drafting, escalation, and a human review queue in production behind a flag.
-
04
Handover
1 week
Runbook, eval harness, dashboards, and a model-change checklist your team can own.
What you get
- A working triage pipeline connected to your existing helpdesk.
- A versioned eval set and a regression check for every model or prompt change.
- Escalation rules, confidence thresholds, and a human review queue.
- Cost and quality dashboards, not a demo video.
- A runbook for rollback, vendor change, and incident response.
Guardrails: PII redaction, no autonomous refunds or account changes, human approval for irreversible actions, and no lock-in to one model vendor.
Questions
Will this replace support agents?
No. It removes repeatable work and gives agents better context. Edge cases stay human.
Which helpdesk and model do you use?
Whatever you already run. The pipeline is model-agnostic and integrates through your helpdesk’s API.
How is success measured?
Resolution rate, escalation rate, cost per resolved ticket, latency, and eval pass rate against the agreed failure budget.
Start
Book a fixed-scope audit. You leave with a ranked opportunity list, a cost baseline, and an eval plan — whether or not we build together.