under 1s
Sub-second classification
Category, priority, and owner set the moment the ticket lands — no waiting on a human sort.
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Ticket triage is the bottleneck. AI removes it.
Ticket triage — reading each new ticket, deciding what it is, how urgent it is, and who should own it — is where support time quietly dies. It feels like minutes per ticket; across hundreds of tickets a week it is your largest hidden cost. FlowTux automates triage completely: every ticket is categorized, prioritized, deduplicated, and assigned by Tux AI in under a second.
Sapping HQSR#1291 · Checkout failing for all users
Triage completed by Tux AI in 0.8s — before the queue was opened.
Back to ticketsSoftwareIn Progress
Description
“checkout is broken for everyone since about 10:02, we are getting card declines on the new flow”
Tux AI · triage · 10:02
Triage
CategoryBug / Payments
PriorityHigh — all users affected
DuplicatesMerged with Sentry cluster #4417
Assigned@payments-oncall
Code findings
payments/checkout.tsconfidence 0.94api/stripe-webhook.tsconfidence 0.71Routed to @payments-oncall · SLA clock started · full trail on the timeline
Why manual triage fails at any scale
Manual triage fails three ways at once — and the third one is why nobody fixes the first two.
Slow
Tickets wait for a human to sort them, so time-to-first-action includes queue-sorting time.
Inconsistent
Priority depends on who triaged the ticket and how their day was going.
Invisible
No dashboard shows hours spent deciding what tickets are, so nobody optimizes it.
Manual triage has three failure modes. It is slow: tickets wait for a human to sort them before work can start, so time-to-first-action includes queue-sorting time. It is inconsistent: priority depends on who triages and how their day is going. And it is invisible: no dashboard shows "hours spent deciding what tickets are," so nobody optimizes it.
Rule-based routing ("if subject contains VPN, assign to network") helps until reality stops matching the keywords — which is immediately.
What AI ticket triage does differently
Tux AI reads the ticket the way a senior engineer would — content first, keywords never.
Tux AI reads each ticket by content, not keywords — the way a senior engineer would.
For technical tickets, triage goes further: the linked repository is indexed and the likely files and modules are attached with confidence scores. Assignment weighs owner expertise and current load. All of it lands on the ticket timeline, auditable, before a human has opened the queue.
Triage that ends in resolution
A label is not the point. Most triaged tickets route straight to an outcome.
Input
Triaged ticket
Tux AIclassifies
Known fix runsKB answer sentNoise suppressedHuman, pre-diagnosed
Classification is the means, not the goal: a triaged ticket routes straight to an outcome, and teams typically see around 50% resolve without human sorting.
What you get
by meaning
Semantic deduplication
Duplicates detected by meaning, not string match — across chat, error logs, repo issues, and email.
by impact
Consistent priority
Priority derived from business impact, applied the same way on every ticket.
ranked files
Code-grounded findings
Likely files and modules attached with confidence scores for technical tickets.
skill + load
Load-aware assignment
Routing weighs expertise and current workload, not just a round-robin.
every decision
Full audit trail
Each triage decision is logged on the ticket timeline — nothing is a black box.
Turn on AI ticket triage
- 1
Create your workspace
Free 14-day trial.
- 2
Connect intake
Slack, email, Sentry or Datadog, GitHub or GitLab.
- 3
Link repositories
Unlocks code-grounded findings on technical tickets.
- 4
Compare in suggest-only
A week of AI triage beside your own.
- 5
Enable auto-routing
Then auto-resolution, category by category.
Triage quality is measurable before you trust it: suggest-only mode logs what the AI would have done, next to what your team actually did.
Related
Frequently asked questions
What is ticket triage?
Ticket triage is the process of reading each incoming support ticket and deciding its category, priority, and owner before work starts. Done manually, it is one of the largest hidden time costs in support. AI ticket triage automates the entire step: FlowTux classifies, prioritizes, deduplicates, and routes every ticket in under a second.
How accurate is AI ticket triage?
FlowTux grounds triage in your actual data — ticket history, linked repositories, and past resolutions — rather than generic models alone. Teams start in suggest-only mode to measure accuracy against their own triage, then enable automation per category. Every decision is logged and correctable, and corrections feed back into routing.
What is the difference between rule-based routing and AI triage?
Rules match keywords and break when phrasing changes; they also cannot set priority from impact or detect duplicates by meaning. AI triage reads content: "checkout is broken for everyone" and a TypeError in your error logs route to the same owner as one incident, at high priority, with the likely file attached.
Can AI triage work with my existing helpdesk?
FlowTux syncs bidirectionally with Jira and GitHub, so triage decisions flow into tools your team already uses. Many teams run FlowTux as the triage-and-resolution layer while developers keep their existing issue tracker.
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fighting fires?
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