Use case → Support Ticket Triage

Zero-touch support triage
from the first ticket in.

classifaily reads every inbound ticket, classifies the type, priority, and team - then hands off a structured result your ticketing system can act on automatically. No manual reading. No routing delays.

~3 min
Manual triage time per ticket
<300ms
classifaily triage time
100%
Consistent routing, every ticket

Manual triage is a tax on every support team.

Every minute an agent spends reading, categorizing, and routing a ticket is a minute not spent resolving it. And the problem scales linearly with ticket volume.

Time to first response suffers

Tickets sit in a shared inbox while agents manually read and route them. High-priority issues get buried under lower-urgency ones because nobody knows the difference yet.

Routing errors are inevitable

Agents misread intent. Billing tickets go to tech support. Account issues land on the wrong team. Every misroute creates an extra handoff, an apology, and a delayed resolution.

It doesn't scale

Manual triage headcount grows with ticket volume. Adding agents to sort and route tickets is pure operational overhead with zero customer value delivered.

CSAT takes the hit

Customers waiting in unrouted queues don't care why. They just know nobody got back to them fast enough. Triage delays directly translate to lower satisfaction scores.

Three steps from ticket in to ticket routed.

01

Ticket arrives in your system

Via Zendesk trigger, Jira automation, webhook, or direct API call - a new ticket is submitted and your automation fires.

Zendesk trigger Jira automation n8n / Zapier Webhook
02

classifaily classifies the ticket

Send the ticket subject and body to the API. Get back a structured label - type, priority, department - with a confidence score, in under 300ms.

Sub-300ms Confidence score Explainability
03

Your system routes automatically

Use the returned label to set the ticket's queue, assignee, priority, and tags - all before a human reads a single word. Branch on the result in your workflow or ticketing automation.

Auto-assign queue Set priority Tag & escalate

One call. Full triage output.

Pass the ticket body, reference your saved triage schema, and get a structured classification back in milliseconds. No prompt engineering. No custom model.

Request
triage-ticket.sh
curl https://api.classifaily.com/v1/classify \
  -H "Authorization: Bearer cai_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "type": "text",
    "input": "Subject: Can'\''t log in - keeps saying wrong password\n\nHi, I'\''ve been trying to log in for 20 minutes. I reset my password twice but it still says invalid credentials. This is urgent, I have a client call in an hour.",
    "schema_id": "support_triage_v1",
    "explain": true
  }'
Response
response.json
{
  "status": "completed",
  "result": {
    "label": "account_access",
    "confidence": 0.96,
    "explain": "User explicitly reports login failure after two password resets. Urgency is clear from the time constraint mentioned."
  },
  "meta": {
    "latency_ms": 241
  }
}
Use separate schemas to run multiple classifiers in parallel - one for ticket type, one for urgency, one for sentiment - all from a single batch call.

Define your triage taxonomy once. Use it everywhere.

Save a schema and reference it by ID across all your ticket sources. Change the categories once, and every integration picks it up automatically - no deploys, no config drift.

Ticket type schema
POST /v1/schemas
{
  "name": "support_type",
  "categories": [
    "billing",
    "technical_bug",
    "account_access",
    "feature_request",
    "onboarding",
    "general_inquiry"
  ]
}
Urgency schema
POST /v1/schemas
{
  "name": "support_urgency",
  "categories": [
    "critical",
    "high",
    "normal",
    "low"
  ]
}
Sentiment schema
POST /v1/schemas
{
  "name": "customer_sentiment",
  "categories": [
    "frustrated",
    "neutral",
    "satisfied",
    "at_risk_of_churn"
  ]
}

What changes when triage is instant.

Faster first response time

Tickets land in the right queue immediately. Agents open their queue and see only the tickets they own - already prioritized and labeled. No hunting, no sorting, no reading for intent.

~3 min triage delay → 0

Consistent, error-free routing

Classification doesn't have bad days. It doesn't misread an email because the wording was ambiguous. Every ticket gets the same quality triage decision at 2am on a Friday as it does Monday morning.

0 misroutes from classification drift

Scales without headcount

1,000 tickets a day or 100,000 - the triage time per ticket stays the same. You stop hiring agents to route and start hiring agents to resolve.

Linear volume, flat triage cost

Higher CSAT through speed

Customers notice when their issue reaches the right person without bouncing around teams. Faster time to the right agent directly lifts satisfaction - and reduces "why did you transfer me again?" moments.

Right agent, first time

Urgent tickets surface instantly

Run a separate urgency classifier and flag critical tickets the moment they arrive. Fire a Slack alert, page on-call, or auto-escalate - before the ticket even hits the queue.

Critical issues caught in <1 second

Structured data for reporting

Every ticket classified means every ticket tagged. Your support analytics finally show real breakdowns - what types of tickets are coming in, when, and at what volume. No manual labeling required.

100% categorization coverage

Plug in to your existing support stack.

classifaily is a REST API. If your ticketing system supports webhooks, automations, or triggers - you can add classification in an afternoon without touching your infrastructure.

Zendesk

via Triggers + Webhooks

Create a Zendesk trigger that fires on new ticket creation and calls a classifaily webhook. Use the returned label to set the ticket group, assignee, priority, and tags via the Zendesk API - all in one automation rule.

1 Ticket created → Zendesk Trigger fires
2 POST ticket body to classifaily
3 Webhook delivers label to Zendesk
4 Update ticket group, priority, tags

Jira Service Management

via Automation Rules

Use a JSM automation rule triggered on issue creation to send the ticket's summary and description to the API. Map the returned label to a Jira request type, component, or label, and auto-assign to the right team queue.

1 Issue created → JSM Automation fires
2 Automation calls classifaily via HTTP
3 Response maps to Jira fields
4 Issue routed to correct component/team

Freshdesk

via Automation + API

Freshdesk's Ticket Automations can call external APIs on ticket creation. Wire up classifaily to return a type and priority, then use Freshdesk webhooks to update the ticket's group and label fields automatically.

1 New ticket → Freshdesk automation
2 HTTP call to classifaily classify
3 Use response to update ticket
4 Assign to correct group & agent

Intercom

via Workflow Automation

Use Intercom Workflows to trigger on new conversations. Send the first message to classifaily and use the label to route to the right team inbox, apply conversation tags, or trigger a bot response flow.

1 New conversation starts
2 Workflow sends to classifaily
3 Label determines team assignment
4 Tags applied, bot flow selected

ServiceNow

via Business Rules / REST

ServiceNow Business Rules can trigger on incident creation and call external REST APIs. Invoke classifaily from a Business Rule or Flow Designer action to auto-populate the category, assignment group, and priority fields.

1 Incident record created
2 Business Rule calls classifaily
3 Category + group auto-populated
4 Incident routed per CMDB mapping

n8n / Zapier / Make

via HTTP node

For any system that can send a webhook, automation platforms like n8n, Zapier, and Make bridge the gap. Drop an HTTP node between your ticket source and your ticketing system, add the classifaily call in the middle, and branch on the label.

1 Webhook trigger from ticket source
2 HTTP node → classifaily API
3 Branch/switch on returned label
4 Update ticket in any system

How a triage pipeline looks end-to-end.

classifaily sits between your ticket source and your routing logic - a stateless classification layer your workflows call on demand.

Ticket sources
Email
Web form
Chat
API / SDK
Automation
n8n / Zapier / Make
or native trigger
Classification
classifaily API
label + confidence
Routed to
Billing team
Tech support
Account team
On-call (critical)

Common questions about support triage.

Do I need to change my ticketing system?

No. classifaily is a classification API - it doesn't replace your ticketing system, it augments it. You call the API from your existing automation (Zendesk trigger, Jira rule, n8n workflow) and use the result to update fields in whichever system you already use. No migration, no new tooling for your agents.

How accurate is the classification?

Accuracy depends on how clearly your categories are defined and how distinctive the ticket content is. For typical support categories (billing, technical, account access, feature request), accuracy consistently runs above 90%. You also get a confidence score on every response - if confidence is below your threshold, you can flag for human review rather than auto-routing.

What happens when confidence is low?

Use the threshold parameter to set a minimum confidence floor. Tickets that fall below it return a below_threshold status, and you can route them to a general inbox or flag them for a human triage pass. High-confidence tickets route automatically; edge cases go to a human - exactly the right split.

Can I define my own categories?

Yes - categories are entirely yours to define. Create a schema with your exact department names, priority levels, or custom labels and reference it by schema_id. You can update or extend categories at any time without touching your integration code.

Can I classify ticket urgency and type in the same call?

You can run multiple classifications against the same ticket using the batch endpoint - one call for type, one for urgency, one for sentiment - and get all three results back at once. Alternatively, save a combined schema that includes urgency as part of a multi-label response. Either approach works depending on how you want to structure your routing logic.

Is it fast enough to classify before Zendesk shows the ticket to agents?

Yes. Median latency is under 300ms. When used synchronously in a Zendesk trigger or JSM automation, the classification completes before any agent queue is populated. For async flows with webhooks, you can hold the ticket in a staging queue until the result arrives and then route it - the lag is typically under a second.

Is my ticket data used for model training?

No. Input data sent to the API is never used to train models. Your customers' support content stays private.

What's the cost at scale?

The Growth plan at $79/month covers 100,000 classifications - roughly 3,300 tickets per day. For most support teams that's more than enough headroom. High-volume operations can contact us for an Enterprise plan with unlimited usage and dedicated infrastructure.

Stacking Classification Layers for Support Triage

A single classifier tells you what a ticket is about. Stacking multiple classifiers tells you what it is, how urgent it is, how the customer feels, and whether they're about to churn - before a human reads a word.

Read the guide →

Stop triaging manually. Start routing instantly.

Free plan, no credit card required. Plug in to your ticketing system in an afternoon.