AI Incident Response

Find the fault
before it becomes
a fracture.

Faultline correlates deploys, logs, metrics, and traces into a single root-cause graph the moment something breaks — so your team spends the incident fixing it, not finding it.

Typical war room 6h 42m
With Faultline 4m 51s
Start free trial See how it works →
FIG. 01 — Root-cause graph Live
Root-cause graph for a Checkout API incident Five signals connect to the incident: the DB connection pool is the confirmed root cause; Deploy #4821 and Auth service are still being checked; Redis latency and CDN edge nodes were ruled out. Checkout API 5xx error spike Deploy #4821 14:03 · checking Auth service 14:03 · checking Connection pool Root cause · 94% Redis latency Ruled out · healthy CDN edge Ruled out · healthy
Root cause identified — DB connection pool exhausted, 94% confidence

How it works

From alert to answer, automatically.

  1. Detect

    Faultline ingests every deploy, alert, and anomaly the instant it happens, across your whole stack — no manual instrumentation per service.

  2. Correlate

    AI builds a live root-cause graph, ranking the signals that actually explain the incident — not just the ones that fired loudest.

  3. Resolve

    Responders get a drafted timeline, the likely cause, and a suggested runbook before the war room even fills up.

FIG. 02 — Incident timeline Checkout API · Aug 31
  1. 14:00:03
    Deploy #4821 shipped to production
  2. 14:02:41
    Checkout 5xx rate crosses 2% — alert fires
    Incident opened automatically
  3. 14:02:58
    Faultline correlates signals into a root-cause graph
    5 candidate signals identified — see Fig. 01
  4. 14:03:15
    Root cause identified
    DB connection pool exhausted · 94% confidence
  5. 14:05:22
    Fix deployed
    Connection pool size increased
  6. 14:07:26
    Error rate returns to baseline
  7. 14:07:32
    Incident resolved — total time 4m 51s

Impact, measured

The numbers on-call teams actually feel.

Typical war room 6h 42m
With Faultline 4m 51s

Median time from first alert to confirmed root cause, measured across live incidents like the one in Fig. 02.

92%

Fewer duplicate pages per incident — one responder gets the graph, not the whole rotation.

3.1k+

Signals auto-correlated per incident, across logs, metrics, traces, and deploys.

68%

Of incidents resolved before customers file a support ticket.

<60s

From alert firing to a live root-cause graph — no dashboards to build by hand.

Features

Everything the first responder needs, nothing they don't.

Root-cause graph

Auto-correlates logs, metrics, traces, and deploys into one causal graph — ranked, not just listed.

Live incident timeline

Every signal, deploy, and human action on one shared timeline — the record writes itself as the incident happens.

Smart paging

Pages the one responder who can actually fix it — routed by the graph, not by whoever's on the rota.

Runbook autopilot

Drafts the first response steps from your own past incidents — a starting point, not a generic checklist.

Postmortem autogen

Generates a draft retro — timeline, cause, and impact — while the incident is still warm, not two weeks later.

Status page sync

Public status updates write themselves from the timeline — no context-switching to a second tool mid-incident.

Stop hunting. Start resolving.

Faultline is free to try for engineering teams who'd rather ship than sit in a war room.

Start free trial Talk to an engineer →