Solution Scenario · Service · Automation
Prepare Service Enquiries Automatically without Giving Up Subject-Matter Control.
This solution scenario illustrates how emails and attachments can be recognised, missing information exposed and cases handed over to service, CRM or ticketing systems in a controlled way.
Anliegen, Produkt, Dringlichkeit
Prüfen, ergänzen, vorbereiten
Zuständigkeit, Entwurf, Ausnahme
Illustrative Starting Point
A Shared Inbox Becomes a Manual Distribution Hub.
A technical service team receives enquiries about faults, spare parts, maintenance and documentation. Product, serial number and urgency may appear in the text, PDFs or images. Employees read every message, look up customer data and route each case to the appropriate team.
The target state combines fixed rules with clearly bounded AI tasks: content is structured, known master data is added and an answer or follow-up question is prepared. Uncertain, safety-relevant or commercially sensitive cases remain visibly subject to human review.
Solution Logic
When conventional automation is enough, and when AI adds value.
Production-ready solutions combine deterministic steps, contextual AI tasks and clearly defined human responsibility.
Workflow
Execute Fixed Rules Reliably
Model structured inputs, unambiguous conditions and repeatable actions with conventional workflows.
AI Component
Interpret Unstructured Content
Classify and summarise language, documents or free text, then structure them for the next step.
Combination
Place AI Within a Controlled Workflow
The workflow controls data and states; AI handles a clearly bounded task within the process.
Human in the Loop
Approve Exceptions Deliberately
People review uncertain outputs and decisions with operational, financial or legal consequences.
Scenario Components
The Service Process Needs More Than an Automated Text Reply.
Input
Recognise the Enquiry and Product
Classify messages and attachments and expose the product context, serial number, urgency and missing information.
Knowledge
Use Documentation in a Controlled Way
Provide approved manuals, service notes and known fault patterns with source references for processing.
Systems
Add Customer and Case Data
Query CRM, ERP or the ticketing system and assign recognised information to an existing or new case in a controlled way.
Ownership
Reply, Follow-Up Question or Escalation
Prepare a draft, request missing information or hand the case over to a responsible person with an explanation.
System View
Dependable automation connects inputs, logic and operations.
The visible AI step is only one part. Integrations, states, permissions, logging and error handling determine whether the process works in daily operations.
Inputs
Ingest email, forms, files, APIs or specialist systems in a controlled way.
Orchestration
Control rules, AI tasks, approvals and escalations transparently.
Outputs
Update CRM, ERP, DMS, notifications and monitoring reliably.
Prerequisites
These questions should be answered before a pilot.
Process
Is the Process Clear Enough?
The trigger, outcome, variants, volume and current handling must be described transparently.
Data
Are Inputs Usable and Accessible?
Formats, quality, permissions and technical access are reviewed before implementation.
Exceptions
Where Is Control Required?
Uncertainty, failure cases, approvals and escalation paths are handled explicitly.
Operation
Who Owns the Process?
Business ownership, monitoring, adjustments and incident handling are defined.
Solution Process
From a Shared Inbox to a Controlled Pilot Workflow.
01
Analyse Real Enquiries
Map enquiry types, volume, processing time, required information, systems and critical exceptions.
02
Separate Rules and AI
Define deterministic assignments, context-dependent AI tasks, data flows and human approvals.
03
Test a Focused Pilot
Test selected enquiry types with representative emails and attachments against predefined criteria.
04
Decide on Integration
Evaluate quality, time savings and correction needs before connecting the ticketing system, CRM or additional channels.
Measurement
Automation must improve the process, not merely work in a demonstration.
A baseline is recorded before the pilot. Value, correction needs and operational effort can then be compared realistically.
Effort
Processing Time and Manual Steps
How much active work, waiting time and coordination does a case require before and after the pilot?
Quality
Errors, Corrections and Exceptions
Which outputs are directly usable, which require rework and when is escalation necessary?
Operation
Cost, Stability and Adoption
How reliably does the workflow run, what maintenance does it require and does the team actually use it?
Example Case
A Spare-Parts Enquiry Becomes a Verifiable Service Case.
An email describes a fault and includes a photo of the nameplate. The workflow assigns the sender and equipment, reads the serial number and checks whether product, fault pattern and requested date are described sufficiently. An AI component structures the free text and suggests the appropriate category based on approved documentation.
If the case is clear, a ticket is prepared with a summary and sources. If information is missing or the assignment is uncertain, a responsible person receives the original content, recognised data and reason for review. Every correction feeds into the pilot quality evaluation.
The illustrative scenario makes the solution path tangible. A more detailed technology assessment is provided by the decision matrix for AI agents and conventional automation.
Next Step
Do You Recognise Your Service Process in This Scenario?
In the consultation, we clarify enquiry types, processing effort, knowledge sources, systems and a realistic pilot scope.