- Customer supportIndustry
- B2B services providerClient
- AI AgentsCategory
- Fast to valueTime to impact
The challenge
- A steady, high volume of support tickets has to be read, categorised and routed by hand before anyone can even start solving them, slowing response times and tying up the team on repetitive triage.
An AI agent that triages and helps resolve high-volume support tickets.
An automation that takes incoming support tickets, understands them, and accelerates resolution, from triage to drafted responses.
What we built
- 01An AI agent reads and understands each incoming ticket.
- 02Tickets are categorised and routed to the right place automatically.
- 03The agent drafts responses for common issues to speed up resolution.
How it works
What it can do
Automated triage
Reads and prioritises tickets as they arrive.
Auto-categorisation
Classifies and routes tickets without manual sorting.
Response drafting
Suggests replies for common, repetitive issues.
Who stays in the loop
The call the system deliberately does not take, and what the person is given to take it with.
An automation that takes incoming support tickets
The support agent
Decideswhat is actually sent to the customer
Seesthe drafted reply, the category and route the agent chose, and the original ticket
The payoff
What is different once it is running. No invented numbers: these are the changes the work was built to make.
Tickets arrive already read, sorted and routed, with a draft reply waiting. The team starts at solve, not triage.
Routine triage and sorting handled automatically.
Agents start from a draft, not a blank box.
Faster first response on high-volume queues.
Built with
The layers this runs on, from what comes in to what it plugs into.
- Model layer
- LLM agent
- Connects to
- Ticketing integration
Common questions
The same answers as above, written out.
An automation that takes incoming support tickets, understands them, and accelerates resolution, from triage to drafted responses.
A steady, high volume of support tickets has to be read, categorised and routed by hand before anyone can even start solving them, slowing response times and tying up the team on repetitive triage.
A ticket arrives in the queue. The agent reads, categorises and routes it. A draft reply is ready for the team to send.
The support agent decides what is actually sent to the customer. They see the drafted reply, the category and route the agent chose, and the original ticket.
Model layer: LLM agent. Connects to: Ticketing integration.
Routine triage and sorting handled automatically. Agents start from a draft, not a blank box. Faster first response on high-volume queues.
Where this fits
The practice it belongs to, how an engagement like it runs, and what we have written about the subject.
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