IT service centre managed with one AI

Consultant allocation, SLA, tickets, hours worked, billing: all in chat, integrated.

Managing a service centre with separate tools doesn't scale

A service centre has continuous clients, SLAs to meet, rotated consultants, hours to bill monthly. Separate systems (ticketing + HR + billing) create silos and inefficiency.

Open tickets without visibility on assigned consultant
Monthly allocations renegotiated via email
Hours logged in tools different from ticketing
Billing not reflecting real SLAs
Client reporting built by hand monthly

Service centre orchestrated by one AI

hice.ai unifies ticketing, allocation, hours and billing in one experience. Service manager sees everything and governs by voice.

"SLA status of Generali this month"
"Which open tickets have no assigned consultant?"
"Replace Marco with Luca on Banca Sella service"
"Generate Enel service centre monthly invoice"

Try it in chat

Examples you can ask:

Static demo of hice's AI chat.

What you get

Service catalog

Service catalog with rates, SLAs, support levels.

Ticket integration

Connectors to Jira, ServiceNow, Zendesk.

Service allocation

Consultants assigned to continuous services with SLA coverage.

SLA tracking

Continuously measured KPIs, alerts on breach risks.

Service billing

Monthly based on hours + fixed fee + extra tickets.

Client self-service

Client portal with service status, tickets, reports.

From service catalogue to real profitability

A service centre is run well when every line in the catalogue has, alongside its commercial description, a known cost and an assigned capacity. Without those two figures, margin only surfaces at close and always in aggregate, which is exactly when it can no longer be corrected.

The calculation is not complicated, but it requires connecting three data points that usually live apart: hours actually spent on the service, the cost of the people spending them, and what the contract bills. Once that connection exists, it becomes clear which services sustain the account and which quietly erode it.

Cost per service unit with history, not just this month
Hours booked to the service and not only to the client
Margin per service and per client, reviewed monthly
Alerts when consumption exceeds contracted capacity

SLAs that are met because they are measured where the work happens

A service level agreement only works if the team sees the clock while working, not when the monthly report arrives. That means the SLA definition — what starts the counter, what pauses it, which priorities exist and which time windows apply — must be configured in the same place interventions are recorded.

It is also worth settling the awkward cases before signing: what happens when the client is slow to respond, how a reopened ticket is treated and who decides a priority reclassification. Those three rules account for most disputes about breaches and usually take half an hour to agree.

Explicit definition of counter start, pause and stop
Different priorities and calendars per client and per service
Warning before the breach, not a report after it
Traceability of reclassifications and reopenings

Mixed billing without rebuilding it by hand every month

Most managed-service contracts combine a fixed fee with variable consumption, hour banks or out-of-scope work. Gathering that information at month-end from the ticketing tool, the timesheet and the contract is the usual reason invoices go out late and with discrepancies.

If hours are booked to the service as the work happens and contract terms live in the same system, preparing billing stops being a monthly project. The direct effect shows in cash: pulling invoicing forward by a week on a recurring contract is a stable treasury improvement.

Fixed fee, consumption and extra work in one calculation
Hour banks with balance visible to client and team
Invoice detail agreed at contract signature
Export to the accounting system without manual collection

Managed services provider, 8 enterprise clients, 80 consultants

Service manager spent 2 days/month closing reporting and billing. With hice.ai: 4 hours. 12 person-days/year returned to client governance.

hice.ai vs ServiceNow + HR tool + ERP

Feature	hice.ai	Traditional stack
Single service-consultant view	Yes	No, must reassemble
Real-time SLA	Yes	Periodic reports
Service billing integrated	Yes	Separate tool
Time to close month	Hours	Days
License costs	One	Multiple
AI native	Yes	No