By use case: Ticket triage
AI ticket triage
Every ticket read, labelled and in the right queue before a person opens it, with a draft reply waiting.
- First workflow live
- Classify and route, usually inside the first sprint
- Usually owned by
- Support leads with 2 to 50 agents
- Built on
- Zendesk, Freshdesk, Intercom
- Judged on
- Time to first touch and Reassignments
In short
AI ticket triage reads each incoming ticket, decides its type, urgency and owner, attaches the order or account it concerns, and drafts a reply for a person to check and send. SBD builds it inside the helpdesk you already run. Rules handle what rules can, the AI step handles the rest behind a confidence line, and anything below that line goes to a person with the reason shown.
Who this is for
The people who usually own ticket triage.
- Support leads with 2 to 50 agents
- Operations managers who own the shared inbox
- E-commerce teams with high order-question volume
- Software companies where bugs arrive as support tickets
Is this you?
If three of these sound like your week, this page is about your team.
- A lead spends the first hour of each day assigning tickets
- Tickets are reassigned more than once before an answer
- Urgent tickets are found by accident
- Escalated tickets have no update for days
- An AI tool was tried and switched off after a wrong answer
What it costs today
Where ticket triage loses the hours.
Someone reads every ticket twice
Once to work out what it is and who should have it, then again by the person who ends up answering.
Routing by whoever is free
Tickets are picked from one shared queue, so a billing question waits behind a bug report and lands with the wrong person.
Urgent tickets look like the rest
A cancellation threat or an outage report sits in the same list as a password reset until someone happens to open it.
Escalations go quiet
A ticket sent to engineering or finance leaves the helpdesk, and nobody tells the customer, or the agent, what happened next.
For support teams
Nobody should read a ticket twice.
Send us an export of last month's tickets. We will show you how many could have been routed without a person, and which ones should never be.
Walk us through your queue
By company size
Ticket triage at 10 people, and at 1,000.
- 1 to 10
One inbox, everyone reads everything, and urgent emails are found late.
- 11 to 50
A helpdesk with a single queue and no rules, so routing depends on who looks first.
- 51 to 200
Several queues and tiers, a lead who spends the morning reassigning, and escalations nobody follows up.
- 201 to 1,000
Many channels and languages, SLAs by tier, and a past AI pilot that guessed wrong and was turned off.
What we build
What we build for ticket triage teams.
- 01
Classification with a confidence score
An AI step labels type, product, urgency and sentiment. Above your confidence line it routes on its own. Below it, a person decides and the system records the answer.
- 02
Routing rules you can read
Queues, skills, languages and customer tiers written as plain rules in the helpdesk or the workflow tool, so a team lead can change them without us.
- 03
Drafted replies, human send
A reply drafted from your macros, help articles and the customer's order or account. The agent edits and sends. Edits feed back into the next draft.
- 04
Escalation with a return path
Bugs become issues in your tracker, refunds become finance tasks, and the status of each comes back onto the ticket automatically.
The workflows
The ticket triage workflows, and what sets each one off.
- 01 Classify and route
When a ticket arrives by email, chat, form or WhatsApp
ThenLabelled, scored and sent to a queue, or to human triage if unsure
- 02 Attach context
When a ticket mentions an order, account or invoice
ThenThe matching record pulled onto the ticket
- 03 Draft a reply
When a ticket is assigned
ThenA draft waits for the agent to edit and send
- 04 Urgent flag
When outage, legal or cancellation language detected
ThenPriority raised and a lead alerted in Slack
- 05 Escalation loop
When a ticket is tagged as a bug or refund
ThenIssue or task created, status written back to the ticket
The numbers we move
How a ticket triage build is judged.
Every build has a number written into the blueprint. These are the ones ticket triage builds are measured by, and how we measure them.
| Metric | Before | After | How it is measured |
|---|---|---|---|
| Time to first touch | Hours on busy days | Minutes for routed tickets | Median time from ticket creation to assignment, from the helpdesk |
| Reassignments | Common and not counted | Counted weekly and falling | Tickets moved between groups after first assignment, per week |
| Draft acceptance | No drafts | Tracked per category | Share of drafts sent with light or no edits, sampled weekly |
| Below-line rate | Not measured | Visible and reviewed | Share of tickets sent to human triage because the score was under the line |
Proof
Proof from builds like this.
- Customer story
Property operations automations and agent fleet
An agent fleet with a decision queue and policy engine: routine actions approved in bulk, risky ones always sent to a person.
Read the story - Customer story
Order and dispatch management system
Automated WhatsApp status updates on every order change, so fewer tickets were status questions in the first place.
Read the story
How it starts
An audit of the ticket triage work your team still does by hand.
One to two weeks. We map the workflows, put an hours-a-week figure on each, and give you a costed blueprint in order of payback. The audit is credited in full to the build.
- Week 1 to 2Audit. We sit with the people who do the work and map it.
- Week 3Blueprint. Fixed scope, fixed price, the first build chosen by payback.
- Week 4 onBuild in two-week sprints, working software every second Friday.
- After go-liveSixty days of hypercare, then a care plan or run it yourself.
What this does not do
So the scope is clear before the call.
- Under a few dozen tickets a week. One person reading them is cheaper than any build.
- Fully unattended replies from day one. A person sends until your own numbers say otherwise.
- Replacing your helpdesk. We build inside the one you have.
Terms, defined
Ticket triage terms, in plain English.
- Triage
- Deciding what a ticket is, how urgent it is and who should own it, before anyone answers it.
- Confidence line
- The score above which the system routes on its own and below which a person decides.
- Human triage queue
- Where tickets the system is unsure about wait, with its suggestion and score shown.
Questions
What people ask about ticket triage automation.
Will the AI reply to customers on its own?
Not at the start. It classifies, routes and drafts, and a person sends. Once you have a few weeks of edits to look at, some teams let it send one or two simple categories, with a weekly review sample.
What happens when it is unsure?
The ticket goes to a triage queue with the suggested label and the score. A person picks the right one. Those corrections are how the confidence line gets set for your tickets, not a generic one.
Do we need to change helpdesk?
No. We work in Zendesk, Freshdesk, Intercom, Gorgias or whichever you run, using its own API, tags and views.
How much does it cost?
It starts with the $500 Automation Audit, credited to the build. Triage on one helpdesk with drafting is usually at the lower end of the $5,000 to $15,000 range where most builds land. Care plans start at $50 a month.
What about languages other than English?
Classification and drafting work across the languages the model supports. We test on a sample of your real tickets in each language before routing goes live.
Reading
- Systems
How much should an AI agent be allowed to do?
An agent with an unscoped token dropped a production database and its backups in nine seconds. Our rule: read widely, write narrowly, cap spend, escalate.
- Systems
Six months of AI agents in production: what broke
Not the model. Field renames, a drifting confidence score, a new invoice format and a Slack channel nobody read. What failed in our agents, and what we changed.
- Strategy
We tried AI and nothing stuck
The sentence we hear on most first calls is rarely about the AI. Four reasons small companies abandon tools, and the change that makes the next try stick.
Related
- Function
Customer support
Answer the same question once, put the order on the ticket, and let people handle the conversations that need a person.
- Use case
Document extraction
PDFs, forms and emails read into structured records, checked, and filed where your team already works.
- Use case
Client portals
Customers log in and see their own orders, files and status, so they stop having to ask.
- Industry
Service and e-commerce
One product record on every channel, stock that cannot oversell, orders that reach fulfilment without re-typing, and customers who hear first.
By use case: Invoice processing, Lead routing, Customer onboarding, Employee onboarding, Quote generation, Order to cash, Document extraction, Approval workflows, Inventory sync, Weekly reporting, Client portals
Ticket triage
Get the ticket triage hours back.
Bring the one ticket triage workflow your team still runs by hand. You leave the call with a yes or no on fit and the first thing we would build.
Book the call