Illustrative solution pattern
Service desk triage and resolution
Inbound requests classified, enriched and routed, with straightforward cases resolved from approved guidance and the rest escalated with context.
The challenge
The problem this solves
Service desks spend a large share of their capacity on classification and routing rather than resolution, and a significant proportion of tickets are recurring questions with a documented answer.
Existing process
The limitation being removed
Requests arrive by email, form and telephone in inconsistent formats. Agents read each one, categorise it, look for prior similar cases, and route it — often more than once before it reaches the right person.
The solution
What was built
A triage service that classifies each request, extracts the details the resolving team needs, links to similar prior cases, and drafts a resolution from approved guidance where the request matches a known pattern. Drafts are reviewed before sending; anything unclear, sensitive or novel is escalated with the gathered context attached.
Implementation approach
- Analyse historical tickets to identify the categories and recurring patterns worth automating
- Build classification and extraction, evaluated against a labelled historical sample
- Integrate with the service management system so the triage output lands where agents already work
- Add draft resolution grounded in approved guidance, always subject to agent review before sending
- Set escalation rules for sensitive, ambiguous or novel requests, defined with the service owner
- Report on outcomes, and feed unresolved patterns back into the knowledge base
Technologies used
- Classification and extraction over inbound request text
- Retrieval across approved knowledge and resolved-case history
- Integration with the existing service management system
- Draft-and-review workflow with agent approval
- Reporting on categories, deflection and escalation reasons
Services provided
Applicable sectors
- Government & public sector
- Enterprise
- Education
- Small & medium enterprises
Security and governance
Controls designed into the solution
Decided before implementation. Every one of these is an architectural choice, which is why they cannot be added afterwards without a rebuild.
- No response reaches a requester without a person approving it
- Escalation is mandatory for defined sensitive categories, regardless of confidence
- Draft responses grounded in approved guidance, with the source shown to the agent
- Requester personal data minimised and access-controlled
- Full audit trail of classification, draft, agent decision and final response
- Inbound request text treated as untrusted input, with injection containment applied
Outcome
Expected outcome (design intent, not a measured result)
These are design expectations for this pattern, not measurements from a delivered engagement. We would agree how to measure them with you before building.
- Agent time shifts from classification and routing towards resolution
- Recurring questions get consistent answers drawn from approved guidance
- Escalated cases arrive with context already gathered, reducing back-and-forth
- Category reporting shows where to fix the underlying cause of ticket volume
Related
Other solution patterns
Grounded knowledge assistant
An assistant that answers staff questions from your approved documents, cites its sources, and declines when the corpus does not cover the question.
Read the full write-upDocument intake and extraction
Structured data extracted from inbound documents, with confidence surfaced and a person confirming before anything is committed.
Read the full write-upAutomated compliance checking
Submissions checked against a written rule set, with every finding citing its clause and a competent person confirming the outcome.
Read the full write-upAgentic AI & Automation
AI agents, assistants and automated workflows that carry out real work inside your systems, with human approval at the points that matter.
Managed Services & Support
Advisory, managed IT and application support — the long-term accountability that keeps a delivered system healthy.
Could this work for you?
Tell us how your situation differs from this example. Where a material uncertainty remains, a bounded proof of concept with a pass threshold agreed in advance is usually the cheapest way to find out.
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