Hr ops · Production

Zopa Bank automates HR ticket triage with monday service AI, achieving 98% assignment accuracy and saving 50+ hours monthly

The problem

Zopa Bank's HR Ops team was managing hundreds of weekly employee requests through a shared Outlook inbox with no structured way to assign, prioritize, or track tickets, and no visibility into team performance or response times.

First attempt

The manual tagging and color-coding system in Outlook was unscalable, provided no tracking or accountability, and caused tickets to slip through the cracks.

Workflow diagram · grounded in source
1
Employee emails HR request
trigger
“The team kept the front-end experience for employees exactly the same. Requests still came in via email, but behind the scenes, everything changed.”
2
AI triages by content and tone
ai_action
“Using custom AI prompts, tickets are automatically triaged based on their content and tone.”
3
AI auto-assigns ticket
ai_action
“People get assigned a ticket automatically through the AI using prompts we built. The success rate is about 98 percent.”
4
Automation routes and escalates
routing
“Automations help route tickets to the right person, escalate critical issues, and trigger post-resolution surveys. We have things like: if category equals A, then person B gets assigned. If a priority hits critical, it triggers alerts an…”
5
Post-resolution survey triggered
feedback_loop
“When a ticket closes, a survey gets pushed out.”
6
Real-time dashboard monitoring
output
“The team built dashboards to monitor SLA trends, ticket volume, CSAT scores, and team performance by category, division, or agent.”
Reported outcome

Zopa's HR team now manages over 550 internal requests monthly with 98 percent ticket assignment accuracy, saves more than 50 hours per month, and for the first time measures and reports strong CSAT scores.

Reported metrics
Ticket assignment accuracy98 percent
Time saved per ticketfive minutes per ticket
Hours saved per monthmore than 50 hours every month
Monthly internal requests managedmore than 550
Show all 5 reported metrics
ticket assignment accuracy98 percent
time saved per ticketfive minutes per ticket
hours saved per monthmore than 50 hours every month
monthly internal requests managedmore than 550
CSAT scoresreally strong
Reported stack
monday servicemonday work managementOutlook
Source
https://monday.com/w/customer-stories/zopabank
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Zopa's HR team now manages over 550 internal requests monthly with 98 percent ticket assignment accuracy, saves more than 50 hours per month, and for the first time measures and reports strong CSAT scores.

What tools did this team use?

monday service, monday work management, Outlook.

What results were reported?

Ticket assignment accuracy: 98 percent; Time saved per ticket: five minutes per ticket; Hours saved per month: more than 50 hours every month; Monthly internal requests managed: more than 550 (source-reported, not independently verified).

What failed first in this deployment?

The manual tagging and color-coding system in Outlook was unscalable, provided no tracking or accountability, and caused tickets to slip through the cracks.

How is this hr ops AI workflow structured?

Employee emails HR request → AI triages by content and tone → AI auto-assigns ticket → Automation routes and escalates → Post-resolution survey triggered → Real-time dashboard monitoring.

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