Keep the lights on. Let AI write the runbooks.
Incident comms, postmortems, documentation and status updates handled, while you keep the infrastructure honest.
Where the hours actually go.
Alert fatigue is real
Pages at odd hours, half of them noise, each needing a look anyway. Sleep debt is part of the job description nobody wrote.
Runbooks are always behind
The real procedures live in your head and old Slack threads. Every incident gets fixed, but the documentation never catches up.
Postmortems take longer than fixes
Timeline, impact, contributing factors, action items, all formatted for the review meeting while the next alert fires.
Everyone wants updates mid-incident
Management, clients and support all asking how long while you are still diagnosing. Status comms is a second job during every outage.
Your toolkit inside kiap.ai
Live today inside the super app, or being built on the same API. Everything AI drafts, you approve.
Incident comms drafter
Drafts status updates and stakeholder comms from your incident timeline, so you keep fixing while the messages write themselves.
Postmortem skeleton builder
Assembles timeline, impact and action items from your notes into a proper postmortem for the review.
Runbook builder
Turns your rough notes and terminal history into structured runbooks the next person on call can actually follow.
Client status page
Service status and maintenance windows published to clients automatically, ending the flood of is-it-down emails.
Uptime and SLA reports
Monthly uptime, incident counts and SLA numbers compiled for client or management reviews without the spreadsheet ritual.
Maintenance notices
Scheduled maintenance emails reach affected users on time, every time, with the details that matter.
Alert noise triage
In the worksGroups noisy alerts and suggests which page is real, cutting the 3am false alarms.
A day with AI doing the busywork.
Overnight alerts already grouped and summarised. Two were real, both handled with the linked runbook.
Change request for tonight's deploy: the rollback plan and approval notes are drafted from your last three similar changes.
A P2 incident hits. Status updates draft themselves while you run the diagnosis.
The postmortem from this morning is already assembled. You fill in the contributing factors and action items.
Maintenance window notice went out at six. The deploy runs clean and the rollback plan stays unused.
Questions devops engineers actually ask.
Will AI replace DevOps engineers?
No. Judgement calls during incidents, architecture trade-offs and deep knowledge of your systems stay human. What disappears is the writing layer around the work: comms, postmortems, runbooks and status pages.
Does it plug into our monitoring stack?
The platform works from your alert exports, incident timelines and notes, sitting alongside tools like Datadog, Grafana and PagerDuty rather than replacing them.
Can it help with audit and MAS TRM evidence?
Yes. Change records, incident logs and postmortems are kept in a structured trail, which is exactly what technology risk reviews and client audits ask for.
We have an on-call rota. Does it help the team or just me?
Shared runbooks and the status page help the whole rota. The next engineer on call follows the same documentation instead of waking you up.
Is it worth it for a small infra team?
Smaller teams feel it most. When two people carry the whole stack, the hours saved on documentation and comms are the difference between reactive and proactive work.
Keep the craft. Drop the admin.
See your toolkit running inside kiap.ai. One call, a real walkthrough, no pressure.