Save thousands of dollars per month with our included endpoint monitoring.
I have been talking with many MSP owners, and they want to focus on high impact, revenue generating projects, but low value repetitive issues keep filling their ticket queues.
Most IT tickets slow down before troubleshooting even begins because intake lacks context.
I see vague requests like “VPN issue” or “email not working” turn into follow ups and waiting instead of action.
The real bottleneck is missing context at intake, driven by one-line tickets, missing live signals, and intermittent upstream issues.
NetZen AI helps resolve these repeat requests faster at L1, so you can generate more revenue with your current senior technician. So lets dive in, how?
One-line tickets
Vague requests with no structure
Missing live signals
No real-time environment data
Upstream issues
Intermittent problems across layers
L1 Technician“Half the job is just figuring out what the user actually means.”
Many tickets start the same way. “Email not working.” “VPN issue.”
Strong technicians pause, not because the issue is advanced, but because they first have to decode what the user meant.
Industry benchmarks show that roughly 60 percent of tickets are resolved at Level 1. Most issues are routine. But even routine problems stretch out when the initial request lacks structure.
Each clarification cycle adds delay. If even 10 minutes per ticket are lost in back-and-forth, a 2,000-ticket-per-month service desk loses more than 300 technician hours monthly. That is not a skill problem. It is ambiguity at scale.
MSP Operations Manager“We spend more time gathering data than fixing the issue.”
Even when tickets include more detail, the most important signals are usually missing.
Without live context, technicians jump across RMM dashboards, network monitors, VPN logs, authentication records, and cloud status pages just to build a hypothesis.
The modern IT service path
The ticket rarely reflects this complexity.
In modern IT setups, the issue could originate on the device, on WiFi, inside the VPN, within identity, or in a SaaS platform hosted in another region. The true problem may exist anywhere along that service path.
But the ticket rarely reflects that complexity.
L2 Technician“When I check everything, it looks fine. Then the user calls again.”
Some of the most frustrating tickets are intermittent. “It was slow this morning.” “It disconnects randomly.” By the time IT investigates, dashboards are green.
Intermittent issues are often upstream. Routing instability, DNS delays, ISP congestion, cloud latency spikes, or SaaS degradations can all present as device-level complaints. If troubleshooting begins with the assumption that the endpoint is the root cause, teams waste time eliminating the wrong layer.
Without cross-layer visibility across device, network, and service, root cause identification remains reactive and slow.
This gap is why we built NetZen AI. We did not want ticketing to remain a passive intake form. We wanted intake to become the first intelligent step of diagnosis.
When a user reports an issue, NetZen captures structured details and automatically gathers live signals like device health, network conditions, VPN status, identity, and service context directly into the ticket before investigation begins.
NetZen also looks beyond the endpoint to determine whether the issue is local, network-related, or upstream in cloud and SaaS services. Technicians start with clarity instead of guesswork.
If your team feels capable but queues keep growing, the issue may not be skill. It may be missing context at intake. Close that gap, and everything moves faster.
Want to see it in action?
See how NetZen AI transforms ticket intake into the first intelligent step of diagnosis.