How do you catch the support ticket about to breach SLA?
A support AI Employee connected to your help desk, your issue tracker, and Slack. Every 15 minutes it scans the queue for SLA breaches, VIP accounts, and high severity tickets, routes each to the right team, opens a linked issue when engineering is needed, and posts to an escalation channel. It never closes a ticket or promises a customer a resolution.
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Escalation worthy tickets lack clear signals in a busy queue. An SLA breach requires comparing timestamps, VIP status lives in a system other than the help desk, and a high severity determination depends on actually reading the ticket's content. None of it is visible at a glance, and none of it surfaces on its own. Scanning for the urgent items by hand becomes impractical as soon as queue volume climbs. The tickets that most need to jump the line are exactly the ones that get buried in it, and by the time someone notices, the SLA clock has already run out or a VIP has already been waiting too long.
An AI Employee checks your help desk queue every 15 minutes, evaluating every open ticket against three criteria: SLA breach, VIP account status, and high severity. It routes qualifying tickets to the right teams, opens a linked issue in your issue tracker for engineering problems, and posts alerts to the escalation Slack channel, without ever closing a ticket or contacting a customer.
See exactly how the work gets done.
Runs every 15 minutes from a clean read
A schedule starts a fresh, isolated run every 15 minutes with no memory of previous runs, rechecking the entire open queue against the help desk's current state.
Carries your escalation rules
SLA targets, VIP account lists, severity qualifications, and routing tables live as skills and memory that travel with the AI Employee, so the same criteria apply on every sweep.
Connects the queue, the tracker, and the channel, with permissions you set
It reads and routes help desk tickets, opens linked issues in the issue tracker, and posts Slack alerts. Credentials stay in memory, never written to disk, never exposed to the model.
Routes and alerts only; never resolves or promises
Write access is limited to routing. The AI Employee cannot close a ticket, mark it resolved, or contact a customer, and it never drafts a customer message or states a timeline.
Routes, links, and alerts
Every 15 minutes the queue is rechecked against current SLA clocks, VIP lists, and ticket severity. Qualifying tickets are routed to the right team, engineering problems become a linked issue traceable between ticket and tracker, and the escalation channel gets the alert.
Runs in your environment
Each run happens in isolation inside your own infrastructure; your data never leaves it. Only the routing, the linked issue, and the Slack alert leave.
Permissions you set
Credentials stay in memory, injected at run time, never written to disk, never exposed to the model or the logs.
Route and alert, never resolve
The AI Employee cannot close a ticket or end a customer case; it moves work to the right place and stops there.
No promises to customers
It never drafts a customer message and never states a timeline. A named human owns anything a customer sees.
You own it
The SLA targets, routing tables, and per system permissions are yours, versioned and changed on your terms, not in a vendor dashboard.
Tickets now get caught within 15 minutes of qualifying, routed to the right team, and converted to a linked issue before the next request arrives, while every closure, resolution, and customer message stays with a person.
Every 15 min
Open queue rechecked against the current SLA clock
0 closures
Routes and alerts without ever closing a ticket
1 linked issue
Per engineering escalation, traceable between ticket and tracker
Our free AI audit shows you where AI fits, what your security risks are, and gets your first AI employee working.
How do AI Employees resolve support tickets before a human steps in?
Triages, investigates across product, code, and billing, and resolves what it can, escalating sensitive actions with the diagnosis already attached.
×How do you turn the same repeat ticket into a KB article?
Clusters resolved tickets for recurring questions with no matching article, drafts the highest value gaps from real resolutions, and opens one pull request a week, never publishing on its own.
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How do you keep a shared inbox triaged as mail lands?
Reads, labels, and either drafts a reply from the knowledge base or files a task. Customer facing replies land as drafts, held for a named human to send.
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