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The case at a glance

The situation, what we did, and the result.

IAC.ai: Outcome-based: 40% of IT tickets removed, €1M+ saved a year
The client situation

The challenge

25,000 IT tickets a month, billed per ticket. Multilingual data, and a client that wanted no upfront risk.

IAC.ai: Our data-driven method: from your ticket data to a plan
What we did

Our work

  • Data science on the ticket history, to find what to automate first
  • 70+ AI and automation solutions built and deployed over 3 years
  • Run and improved every quarter, outcome-based
IAC.ai: A pipeline of use cases. Each one goes the same five steps.
The result

What the client got

40%of tickets removed: 10,000 a month
€1M+saved a year
70+solutions live
3 yearsoutcome-based program

Client anonymized under NDA. Figures are delivered results over the 3-year engagement.

How the value was sized

Four numbers size the value, step by step.

IAC.ai: Four numbers size the value: CS 02, step by step
The method
Your baselineOnly what changesOwner sign-off
1
Your volume25,000 IT tickets a month

The real baseline of this case.

2
Automation rate30%

The rate in the business case.

3
Cost per unit€10 a ticket

The ratio in this case.

4
Period12 months

One year of value.

5
Annual value€900K business case a year

7,500 tickets a month removed, €75,000 saved a month. Before implementation cost.

6
Delivered40%: 10,000 tickets a month removed

The business case beaten by 10 points.

Your business case is built the same way, from your own baseline.

In detail

What removed 40% of the tickets

IAC.ai: Five automation levers driving 40% ticket elimination at scale
Why this approach worked

A live production pipeline of 70+ AI and automation solutions was built and fed with data all the time. It beat every committed target.

Why it mattered for the client
  • Every target beaten: 40% automation against 30% planned, €1M+ a year delivered against a €900K business case.
  • Zero financial commitment for the client, incentives tied to outcomes, and a path from unstructured data to live automation in production.
Filtering

Smart ticket filtering

AI removes noise and duplicates, stops tickets for issues already known, and removes tickets with no value.

Much lower ticket volumeA cleaner queue for support teams
Correlation

Smart ticket correlation

Related tickets are linked, so no one investigates them by hand.

Less manual investigationOne ticket, one root cause
Self-healing

Intelligent self-healing

Recurrent issues are fixed with no manual work. Bots detect and resolve them before tickets escalate.

Zero-touch incident resolutionProblems prevented
Virtual agent

Virtual agent self-service

End users solve common IT issues themselves, without raising a ticket.

More self-serviceLess frontline support demand
Process improvement

Process improvement

Existing IT support workflows made leaner, to resolve issues faster.

Faster resolution cyclesBetter SLA adherence
IAC.ai: Managed services: we run it for you, under an SLA
The offer behind this result3.2 Managed services

We host, run, support and improve your AI and automation. You get service levels, not tickets to chase.

For youOutcome-based
Steps we owned
DiscoverDecideBuildGo liveRun & improve
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