Sixty client companies, one inbox, and SLAs ticking on every message. Every email and portal request now becomes a categorized, priority-scored ticket in under a minute, routed to the right technician — and SLA breaches have dropped 83%.
Typical results
60
Client companies, one queue
Under 1 min
Email to prioritized ticket
4%
Misrouted tickets, was 22%
Figures reflect typical results for this kind of automation.
The challenge
Requests from 60 client companies poured into a shared inbox where dispatchers triaged by hand — around 45 minutes per ticket at peak, with 22% landing on the wrong technician. Each client had different SLA terms nobody could track in their head, so roughly 35 tickets a month breached deadline, triggering penalty credits and awkward account reviews.
Before and after
SLA breaches per month
−83%Time to triage a ticket
−98%Misrouted tickets
−82%The automation
We connected every intake channel to one pipeline. Each email and portal request converts to a ticket and is deduplicated against open work. AI classifies the category and urgency, reads which client it belongs to, and scores priority against that client's SLA terms before assigning the right technician by skill and load. Countdown timers track every deadline and escalate to a service manager before a breach — not after — while clients get acknowledgments and status updates.
How it works
- 01
Every request becomes a ticket
Emails and portal requests convert on arrival and are deduplicated against open work.
- 02
AI classifies and scores
Category, urgency and affected systems are detected; priority is set against that client's SLA terms.
- 03
Routed to the right tech
Assignment weighs skill, client familiarity and current workload.
- 04
Countdowns watch every SLA
Timers escalate to a service manager before a deadline breaks — not after.
- 05
Clients stay informed
Acknowledgments and status updates go out automatically at every stage.
Starts from
- Client emails
- Portal requests
Delivers
- Categorized, scored tickets
- Right technician assigned
- Pre-breach escalations
The impact
SLA breaches fell 83%, from about 35 a month to six, and penalty credits nearly disappeared. Triage that took dispatchers 45 minutes happens in under one, misrouted tickets dropped from 22% to 4%, and technicians open each ticket with priority, history and SLA clock already set.
Questions about this automation
How does the AI know which client and SLA a request belongs to?
It reads the sender's address, domain, signature and the request text to match the message to a client account. That client's SLA terms are then applied to the detected category and urgency to set priority and a deadline. Requests it cannot match with confidence go to a dispatcher instead of being guessed.
How is the right technician chosen?
Assignment weighs three things: the skills the ticket needs, who already knows that client's environment, and each technician's current workload. Duplicate requests are merged with the open ticket instead of creating new work. Dispatchers can still reassign any ticket, and the rules can be tuned as the team and client list change.
What happens before an SLA deadline is missed?
Every ticket runs a countdown based on the client's terms. When a deadline gets close and the ticket is still open, the automation escalates to a service manager so there is time to act. Clients receive an acknowledgment on arrival and status updates as the ticket moves, without anyone writing them.