A
Experience our Helpdesk AI for 24/7 Facility Service AutomationEvery job follows the same path: request, assignment, work, supervisor review, close. Technicians know what is next, supervisors see what is late, and every asset keeps its full service history.
A CMMS (Computerized Maintenance Management System) is software that manages maintenance work: creating and assigning work orders, scheduling preventive maintenance, tracking technicians and spare parts, and recording each job against the asset it was done on. ADOX AI CAFM includes a CMMS where every job, reported or scheduled, needs a supervisor's approval before it closes. It is built in Riyadh, with a full Arabic interface for technicians across the Kingdom.
A closed job should mean the work was done. In many maintenance teams it only means someone pressed a button. That gap is where repeat call-outs, disputed invoices, and failed audits come from.
In ADOX AI CAFM, every job starts as a service request, from a helpdesk report or a maintenance schedule. A supervisor assigns it and it becomes a work order in the technician's list. The technician accepts or declines, starts on site, pauses if waiting on parts, and marks it complete with notes on what was done.
Technicians cannot close their own work. A supervisor reviews each job and either approves it or sends it back. Every job gets a unique reference, a response target by priority, and an automatic entry in the asset's maintenance history. The result is a record you trust, because a closed job always means someone checked it.
The same four problems come up in almost every first conversation we have in Riyadh.
Jobs get marked complete from the car park. The tenant calls back the next day with the same fault.
Without response targets, a high-priority leak and a squeaky door wait in the same queue.
Two people raise the same request, or a job gets forgotten after a shift change. Paper and chat cannot keep up.
Job sheets end up in a drawer, so nobody can see that an asset has failed five times this year.
Built on the same records your team already uses every day, so nothing has to be entered twice.
Request, assign, accept, start, pause, complete, review, close. Every status is tracked with a timestamp.
No technician closes their own job. Supervisors approve or send work back with notes.
Each job gets an expected response time, so overdue work surfaces before it escalates.
Technicians see their assigned jobs, update status from site, and request parts in the same flow.
Scheduled maintenance creates jobs automatically and follows the same rules as reported work.
Closing a job adds it to the asset's maintenance history. No separate logging step.
Every job in ADOX starts as a service request, either reported through the helpdesk or created by a maintenance schedule. A supervisor assigns it, and it becomes a work order in a technician's list with a unique reference number.
The technician accepts or declines, starts work on site, pauses if waiting on parts, and marks the job complete with notes. Reported and scheduled work follow the same steps, so supervisors manage one queue instead of two.
Technicians cannot close their own work. Each completed job goes to a supervisor, who approves it or sends it back for rework with a note. The job returns to in progress until it is done properly.
This single rule changes the quality of your data. A closed job always means someone checked it, which is exactly what clients, auditors, and your own management need to trust the numbers.
Every job gets an expected response time based on its priority, so a water leak in a hospital corridor does not wait behind a loose door handle. Late jobs are visible before they turn into escalations, and SLA performance appears on the dashboard by site.
Closing a job adds it to the asset's maintenance history automatically. Over time you get a clean record per asset, which feeds reporting and the AI insights that flag repeat failures.
An issue is reported or a schedule comes due, creating a service request.
A supervisor assigns it, and it becomes a work order for a technician.
The technician accepts, works, pauses for parts if needed, and completes.
The supervisor reviews and closes it, and the asset history updates.
What changes when the work moves out of spreadsheets, chat groups, and paper sheets into one system.
| Spreadsheets & legacy tools | With ADOX | |
|---|---|---|
| Job tracking | Paper sheets and chat messages | Every job with a unique reference |
| Closing jobs | Technician marks it done | Supervisor reviews and approves |
| Priorities | First come, first served | Response targets by priority |
| Parts delays | Job disappears from view | Visible as waiting on parts |
| Asset history | Rebuilt by hand when needed | Written automatically as jobs close |
Built in Riyadh for Saudi Arabia: Arabic and English interface, hosting inside the Kingdom, and records that hold up in front of clients and auditors.
Supervisor review catches incomplete work before the tenant calls back.
Response targets by priority show what is slipping while there is still time.
Every job gets a unique reference number the moment it is created.
Clean job history per asset feeds reporting and the AI insights layer.
Hospitals prioritize patient-area jobs, enforce sign-off, and keep a clean maintenance record for accreditation.
Hotels route room faults to the right technician fast and confirm the fix before the room goes back on sale.
Plants track breakdown and planned work on production equipment, with parts requests tied to each job.
Mall maintenance teams handle tenant and common area jobs from one queue, with response targets by priority.
Six questions to ask any vendor before you sign, including us.
Look for clear statuses from request to close, with timestamps on each step.
If technicians can close their own jobs, your completion data will not be reliable.
Urgent jobs need tighter targets, and late jobs should be visible early.
Scheduled and reported jobs should run through the same process.
A job waiting on parts should stay visible and resume when parts arrive.
Field teams in Saudi Arabia need a full Arabic interface, not translated labels.
Common questions about ADOX CMMS in Riyadh and across Saudi Arabia.
A CMMS manages maintenance work: it creates and assigns work orders, schedules preventive maintenance, tracks technicians and spare parts, and records each job against the asset it was done on.
No. When a technician completes a job, it goes to a supervisor for review. The supervisor approves it or sends it back for rework.
Both follow the same process. A scheduled job is created automatically when maintenance falls due, then moves through assignment, work, and review like any reported issue.
Yes. Each job receives an expected response time based on its priority, and SLA performance is shown on the dashboard.
Yes. The CMMS is part of the platform, alongside asset management, inventory, helpdesk, and facility management, so all maintenance data lives in one system.
Yes. ADOX is headquartered in Al Malaz, Riyadh, and our CMMS is used by maintenance teams across Saudi Arabia. The interface runs in Arabic and English, and data can be hosted inside the Kingdom.
CMMS is part of the ADOX platform, and pricing is quoted based on the number of sites, assets, and users. Contact our Riyadh team for a quote that fits your operation.
CMMS focuses on maintenance work: work orders, schedules, technicians, and parts. EAM covers the full asset lifecycle, including purchase, depreciation, and retirement. ADOX includes both, with asset management and CMMS sharing the same records.
Schedules that create jobs on their own. Set the frequency and checklist once, and the right technician gets the task when it is due.
Learn more →Spare parts and supplies tracked across every store and site. Stock moves with jobs, purchase orders, and transfers, with every change recorded.
Learn more →One AI-assisted system for your buildings, assets, maintenance, and helpdesk. See what needs attention across every site before it turns into a complaint.
Learn more →Join 500+ GCC enterprises using ADOX AI CAFM to reduce costs, eliminate downtime, and build smarter facilities. Deployment starts in 4 weeks.
