AI Incident Responder for on-call teams

Engineers get to fix instead of route. It triages by severity, runs your runbooks, keeps stakeholders posted and drafts the post-mortem.

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Webhooks come in and on-call gets paged. Your agent triages by severity, runs your diagnostic runbooks, keeps stakeholders informed and files the post-mortem draft, so your engineers spend their time fixing.

Your AI incident responder, the first line of on-call that never sleeps

Most incidents waste the first 10 minutes on routing. The alert fires. On-call checks whether it matters, pages the right engineer, updates stakeholders, pulls the runbook and kicks off diagnostics, the same way on every incident. Fasrad’s AI incident responder automates those ten minutes.

Webhooks from Datadog, Sentry, PagerDuty, Grafana and custom monitors hit your agent. It classifies severity using rules you configure and pages the right on-call via Slack, SMS or email. Then it runs the associated runbook (`kubectl get pods`, check the deploy log, ping the health endpoint) and posts a status update to your incident channel before a human has opened a laptop.

What it does:

Alert ingestion. Webhook-compatible with every major monitoring tool.
Severity-based routing. P1 pages on-call, P3 emails the team, and noise gets dropped silently.
Runbook execution. HTTP calls, status checks and diagnostic dumps run and get attached to the incident.
Stakeholder updates. Status posts go out automatically at set intervals during active incidents.
Post-mortem draft. Timeline, root cause and remediation get logged and drafted for you to edit.

Your agent has memory of every past incident: which alerts fired together before, which remediations worked, which on-call responded fastest. Over months it becomes the institutional incident memory your team never had time to build.

It sits beside our admin-agent (recurring tasks) and compliance-monitor (policy drift). The incident responder is alert-driven automation. It runs when things break and stays quiet when they don’t.

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Frequently asked questions

What monitoring tools does it integrate with?

Any tool with webhook outputs: Datadog, Sentry, PagerDuty, Grafana, Uptime Robot and custom monitors. Point the webhook at your agent and define the payload schema once.

Can it page SMS / Slack?

Yes. Slack and email are native. SMS goes through a Twilio integration (HTTP request tool), and voice call paging goes through a PagerDuty webhook.

How does it run runbooks?

Runbooks are natural-language instructions plus HTTP request steps (`curl the health endpoint`, `check this Grafana query`). Your agent executes them and attaches the results to the incident record.

Will it make changes in production?

Only if you explicitly configure a runbook step to call a production endpoint. By default it does read-only diagnostics and paging.

What about post-mortems?

Every incident logs a timeline. Your agent drafts a post-mortem with root-cause analysis and remediation suggestions for you to finalize.

Can it replace PagerDuty?

For small teams, yes. At enterprise scale with complex escalation policies, it works better as a layer that adds intelligence on top of PagerDuty’s routing.