Use case
Service triage
From inbox to released answer: the agent classifies, pulls customer, asset and contract history, drafts with sources. A person releases.
01The problem
What the work looks like today
Requests arrive by email, portal and phone note. Someone reads each one, guesses the category, searches three systems for context, and either answers or forwards. In a service desk with 500 to 2,000 requests a month, that is two to four people routing and looking things up instead of solving anything.
02Failure modes
Where time and quality are lost
Three patterns we see in almost every operation of this kind.
- 01
Misrouted requests bounce between teams for days
- 02
The same question is answered differently by different people
- 03
Escalation happens by gut feeling, not by rule
03The agent
What the agent does, step by step
Reads the incoming request, classifies it by type and urgency, pulls the customer, asset and contract history from the CRM and ERP, retrieves the relevant documentation, and drafts a response with its sources. Routine cases are prepared for one-click release; anything outside the rules is queued for a person with the full context attached.
04Human checkpoint
Where a person decides
In the first phase a service agent or engineer releases every customer-facing answer. Release rights widen per category once the acceptance numbers hold. Complaints, safety-relevant topics and contract questions always go to a person.
05Control set
What is enforced and logged
Read access to CRM, ERP and documentation; write access only to the ticket system. Every draft carries its sources. Every release is logged: who, when, what was changed. Confidence below the threshold means no draft, only a routed case.
06Measurement
What the monthly report shows
Four numbers, against the baseline from the assessment.
- 01
First-response time
- 02
Share of cases released without edits
- 03
Misrouting rate
- 04
Handling time per case
Questions
Common questions
How does an AI agent classify service requests?
Which ticket systems does service triage work with?
When does the effect become measurable?
Where to go next
Service
Workflow Build
This workflow in production in 8 to 12 weeks, with its control set.
Service
Workflow Assessment
First check whether this workflow is the right first one for you.
Guide
AI ticket triage for technical service: schema, thresholds, controls
How an AI agent classifies incoming service requests by type, urgency, asset, contract and language, attaches context from the CRM and ERP, and hands uncertain cases to a person with that context in place.
Guide
AI agents in manufacturing: ten examples from service, quality and procurement
An AI agent in a manufacturing company takes over steps in the ERP, CRM and QM system, with a named owner and clear release points. The strongest first candidates sit in service, quoting, quality, procurement and order entry, not in machine control.
Guide
AI agent vs chatbot: the difference between answering and acting
A chatbot answers; an AI agent acts in your systems. Which design fits which process depends on trigger, write rights and release, and the simpler option is often the right one.
Next step
Strategy call
Clarify whether this workflow fits your priority.