If it pages you,
your AI already caught it.
Your AI watches every server, log and metric, all night. It works out why before it wakes anyone, and asks before it changes anything that matters.
Found early. Explained in plain English. Fixed with your OK.
54%.
of respondents say their most recent significant, serious or severe IT outage cost more than $100,000
What your AI does about it:
It watches your servers overnight, works out why a disk or queue is filling, and asks you before it clears anything.
$300,000+.
is what one hour of downtime costs for over 90% of mid-size and large enterprises
What your AI does about it:
It catches a problem at 05:58, fixes what it is allowed to, and pages your on-call person if it can't, before the working day starts.
Imagine it. Here it is.
How AI monitors IT infrastructure overnight
The same board your AI watches all night. Here it catches a disk filling up, works out why and asks before it clears anything.
Mail Service
INCIDENTPrimary provider degraded since 17:14. Fallback to SES active. No customer impact.
4 upstream · 0 downstream
What the on-call rotation covers
Six disciplines. One on-call rotation.
Three incident reports we wrote
Where stacks were on fire. Then weren't.
30 servers, no observability
P1 INCIDENTState before
No central monitoring meant outages were discovered by customer complaints. Senior engineer paged four nights a week. Root causes always elusive.
State after
Prometheus + Grafana rolled out. Alert routing to on-call rotation. Pages dropped 70% in the first month. Engineers slept.
Runbook · Observability rollout · 8 weeks · 3 engineers
Deploy fear
P2 INCIDENTState before
Releases happened once a fortnight, after-hours, with rollback meaning a database restore. Engineers refused to touch prod on Fridays.
State after
Blue-green deploys via GitHub Actions. Database migrations gated. Eleven safe deploys in week one. Friday releases became boring.
Runbook · CI/CD modernisation · 4 weeks · 2 engineers
Backup theatre
P1 INCIDENTState before
Client paid for offsite backups. Quarterly DR test revealed nothing had been restorable for 14 months. Backup job had been silently failing.
State after
Switched to immutable backups + monthly restore drills. Restore time now 22 minutes, tested, signed off.
Runbook · Backup + DR overhaul · 6 weeks · 2 engineers
The tools the on-call team trusts at 3am
What's on the control panel.
Open source by default. Your repo, your cloud, your data.
What an engagement looks like, week by week
Five steps. Then you own it.
Inventory
Map every system, every dependency, every owner. First deliverable is a diagram you can hand to a new hire and they understand the stack.
Observe
Roll out monitoring first. We need a baseline before we change anything. Two weeks of data tells the truth that 'it feels slow' doesn't.
Stabilise
Top three pain points fixed. Pager noise reduced. Deploy pipeline trusted. The team stops dreading prod work.
Automate
Repetitive ops moved to code. Backups, scaling, certificate rotation, OS patching. Humans for judgement, code for the rest.
Handover
Runbooks, dashboards, repos, credentials, on-call rotation. You can keep us, you can fire us, you can hire your own. The system runs either way.
Now it's real.
Four things stay true, whatever we build for you.
Your hardware or ours
On your server, on ours, or on a machine in your office running an open model. Your call.
A person approves what matters
Payments, deletions and anything going to a client wait for a yes from you or someone you choose.
Every action logged
You can see what it read, what it did and why, for every task.
Built with POPIA in mind
We set it up the way we set up any system that handles personal information, with the same care our compliance work gets.
AI infrastructure monitoring questions people ask
How does an AI monitor infrastructure overnight?
It reads the same dashboards an engineer would: Zabbix or Prometheus metrics, logs, disk and queue depth. When something drifts, it checks related systems, works out the likely cause, and asks before it changes anything.
Will it fix things on its own?
Only with your say-so. Read-only checks and diagnosis happen automatically. Anything that changes a system, clearing logs, restarting a service, waits for a person to approve it, even at 3am.
What monitoring stack do you use?
Open source by default: Zabbix or Prometheus and Grafana for metrics, Loki for logs. Self-hosted on your infrastructure, so there's no per-node licence fee and the AI can read straight off it.
Can you take over an existing environment, or only build new?
Both. Most engagements start with mapping what's already running, then layering monitoring and automation on top before touching anything.
What's your response time when something breaks?
Depends on the tier you sign up for. Critical outages get picked up within 30 minutes, 24/7. The AI usually flags the cause before the alert even reaches a person.