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Support Operations
AI Ticket Classification
Every incoming ticket tagged by topic, product, urgency and sentiment the moment it lands, with no agent reading it first.
Every ticket that lands untagged costs someone a read before anything else can happen. This workflow reads each new ticket as it arrives and tags it by topic, product, urgency and sentiment, writing the tags back to your helpdesk. Uncertain tickets are left for a person to triage. Your reports become reliable, and routing, escalation and staffing decisions finally rest on consistent data.
- Every ticket tagged by topic, product, urgency and sentiment
- Tags written back to your helpdesk as tickets arrive
- Uncertain tickets left for human triage, never guessed
$2,400
20–30 working days
Optional maintenance $249/mo
What it is
AI Ticket Classification reads each new ticket as it arrives and tags it by topic, product, urgency and sentiment, before any agent touches it. It runs quietly in the background against your helpdesk, with no customer-facing channel of its own. Every tag it applies is recorded in a run history you can audit.
Why businesses buy it
Manual tagging is inconsistent: different agents choose different tags, busy days mean no tags at all, and your reports quietly stop meaning anything. Every downstream process, from routing to staffing plans, suffers from it. After launch, tickets are tagged the same way every time, and you can see which products, topics and moods drive your volume. The Scope Card spells out the categories, connected systems and confidence rules before you order, so you know exactly how each tag is decided.
Problems this solves
Agents spend the first minutes of every ticket working out what it is
Each new ticket is read as it arrives and tagged by topic, product, urgency and sentiment. Agents open tickets that are already labeled, before anyone has touched them.
Reports are unreliable because tags are missing or inconsistent
The same classification rules are applied to every ticket by one background workflow. Your reports can draw on tags set the same way every time.
Angry or urgent tickets hide among routine requests
Urgency and sentiment tags let your helpdesk views surface upset or time-critical tickets. Every tag the workflow applies is recorded in a run history you can audit.
A good fit if
Tickets currently get tagged inconsistently, or not at all, because whoever picks them up is in a hurry.
You want to route, prioritize or report on tickets by topic and urgency but the tagging step is the bottleneck.
Your helpdesk already supports custom fields or tags, and you just need them filled in reliably.
You care about sentiment as a signal, for example flagging tickets that read as angry even before urgency is judged by keyword alone.
Not the right fit if
You also want the ticket sent straight to the right queue or agent, not just tagged. See AI Ticket Routing, which we often pair with this build.
Your real gap is spotting tickets that need escalating to a manager or a senior tier. See AI Escalation Agent, which is built specifically for that.
You want a customer-facing agent that answers questions, not a background classifier. See AI Helpdesk Agent.
Your classification needs span more than three connected systems or more than twelve workflow steps. Talk to us through our Custom AI enquiry form.
How it works
- A new ticket lands in your helpdesk exactly as it does today, with no change to how customers contact you.
- The classifier reads the ticket text and checks it against the topic and product categories you defined.
- It scores urgency using the signals you agree on, such as wording, repeat contact, or account type, not a single keyword rule.
- It reads sentiment, flagging tickets that sound frustrated or urgent even when the wording is calm.
- Every tag is written back into your helpdesk's own fields, so your existing views, reports and routing rules keep working.
- Anything the classifier is unsure about is flagged for a person to confirm rather than tagged with false confidence.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- A list of the systems involved, with admin or API access to each one.
- A written description, or a short screen recording, of how tickets are tagged manually today.
- Five to ten real sample tickets covering your typical topics and urgency levels.
- The name of who should be alerted if the classifier hits an error or an unusual case.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake.
- One decision-maker who can confirm scope questions during the build.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake reviewed, categories and urgency signals confirmed.
Weeks 1–2
Classification logic and field mapping built.
Week 3
Helpdesk and reporting systems connected and tested.
Weeks 3–4
Twenty test runs on your sample data, with results sent to you.
Week 4
Your review, plus two rounds of requested changes.
Go-live
Live tagging new tickets, recorded handoff session, support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $2,400 |
| Express | 15–25 working days | $2,900 |
| Rush | 10–20 working days | $3,350 |
What you receive at handover
- The classification workflow running in the background against your helpdesk, with no customer-facing channel
- One workflow of up to twelve steps, including one AI decision step, with prompt and guardrail configuration
- Connections to up to three of your systems
- Test report from 20 test runs on your sample data
- Admin guide, recorded 45-minute handoff session and 30 days of post-launch support
Expected benefits and how to measure them
- Agents can start on tickets without sorting them first.
- Reporting by topic and product can become more reliable.
- Upset or urgent customers can be spotted sooner.
- Tickets with complete tags
- Report on the share of new tickets with topic, product and urgency set. Compare four weeks before and after launch.
- Tag corrections by agents
- Sample tickets each week where agents changed a tag, using the run history and ticket audit log.
- Reply time on urgent tickets
- Compare first reply time on high-urgency tickets for the month before and after launch.
Before you start: Record how many tickets currently carry complete tags and the first reply time on tickets you consider urgent.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running AI Ticket Classification costs roughly $20 to $100 a month, covering the automation platform and AI model usage together. Ticket volume is the main driver of where in that range you land.
AI usage during the build and every month after runs through your own accounts, so the cost and the provider relationship both stay visible to you.
Ask about running costsCustom requirements
If your tagging logic needs more than three connected systems, more than twelve workflow steps, or a category scheme this Scope Card does not cover, add a note at checkout for a written Change Quote. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
Monthly maintenance covers monitoring, fixes, model and platform updates, a monthly health report and change hours for work such as a new category or an adjusted urgency signal. It starts after the post-launch support period, bills monthly and can be cancelled any month.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A helpdesk automation rule engine bills per workflow or per monthly run | A custom agency quotes after discovery calls | Ours is one fixed price, shown on this page before you buy |
| Scope | A generic rules tool needs every category and threshold configured by hand | An agency agrees scope during the project | Ours is written on the Scope Card before purchase |
| Delivery | An automation platform can connect in days but the classification logic still has to be built | An agency build usually takes several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
| Sentiment reading | Most rule-based tools only match keywords, missing calm-sounding but urgent tickets | An agency build depends on what was agreed | Ours reads sentiment as its own signal, not just keyword matches |
Questions about this product
Does AI Ticket Classification change what customers see when they submit a ticket?
No. It runs entirely in the background against tickets that already arrived through your normal channels. Customers see no change at all. The only difference is that each ticket now carries topic, product, urgency and sentiment tags written into your helpdesk's own fields, ready for your existing reports and rules to use.
What does AI Ticket Classification cost to run each month?
Roughly $20 to $100 a month, covering the automation platform and AI model usage together. Ticket volume is the main factor, with higher volume sitting toward the top of that range. You pay these providers directly in your own accounts, with no separate per-ticket fee from us.
How long does AI Ticket Classification take to launch?
Delivery runs on a fixed schedule from a verified intake, and the exact date is shown in the delivery panel before you buy, with express and rush options if you need it sooner. Every option includes the same twenty test runs against your own sample data before the classifier starts tagging live tickets.
What systems does AI Ticket Classification need access to?
Up to three systems, typically your helpdesk plus a CRM or spreadsheet used for reporting, with admin or API access to each. Sandbox or test records work for the build itself. Every credential is shared by adding our team as a user or creating a key you control, never sent by email, and access can be revoked at any time.
How accurate is the sentiment and urgency scoring?
We test it against twenty runs on your own sample data before launch and send you the results for review before anything goes live. Anything the classifier is genuinely unsure about is flagged for a person rather than tagged with false confidence, which keeps error rates visible instead of hidden.
Can I add a new ticket category after launch?
Yes, through monthly maintenance. Its change hours usually cover a new category or an adjusted urgency rule. The hours scale with the build, and anything bigger goes through a Change Quote first. Share a few real sample tickets for the new category so it is tested on your data. Maintenance starts after post-launch support and can be cancelled any month.
Can AI Ticket Classification also route the ticket to the right team?
Not on its own. Classification and routing are built as separate, focused workflows so each stays simple and reliable. See AI Ticket Routing, which reads the tags this build produces and sends the ticket on. Ordering both together gives you one connected pipeline.
Guides on this topic
All guides Stop letting untagged tickets slow everything downstream.
Order AI Ticket Classification and every ticket is tagged consistently on arrival, giving your routing and reporting data you can trust.
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