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AI incident intelligence

Find the root cause in minutes, not hours.

Designed to replace 2am trace archaeology with an evidence-linked diagnosis.

OpenTelemetry ingestioncloud analysisair-gapped verify enginegit hook / CI
VP EngineeringHead of SREAI platform leadData protection officer
incident #482 · sev2
14:02 · DETECTED
Timeout spike

errors 0.4% → 7.9%

14:03 · EVIDENCE
14 signals correlated

structural deltas only

14:04 · ROOT CAUSE
Downstream rate-limit change

links to its evidence

14:05 · FIX
Circuit breaker

from recorded outcomes

14:31 · VERIFIED
Back to baseline

outcome recorded

Illustrative incident timeline — real pipeline stages

The problem

Dashboards show symptoms. Root cause is archaeology.

An engineer still spelunks traces at 2am — and the same failure recurs next month with a different on-call.

The solution

Evidence graph in. Diagnosis and fix out.

Incidents are detected from structural telemetry, correlated into an evidence graph, and diagnosed — with the highest-confidence fix from recorded outcomes.

How it works

Alert → telemetry → evidence → root cause → fix → verified.

alerttelemetryevidenceroot causefixverified
What changes

What changes after you adopt it.

Designed to shorten time-to-root-causeWalk into the incident channel with a diagnosis and its evidence.

Repeat incidents stop repeatingVerified fixes are remembered — the second occurrence is cheap.

Customer data stays out of RCAThe payload-free contract makes the privacy conversation short.

Changes verified before they shipA deterministic, air-gapped engine gates non-compliant changes in CI.

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Capabilities

Judgment and memory, wired together.

Payload-free by contract

Structure, never content — enforced by the schema.

Evidence graph

Every conclusion points at its supporting signals.

Compounding fix intelligence

Recorded outcomes show which fixes actually worked.

Deterministic verify engine

Air-gapped checks with reproducible, hashed evidence.

OTel-native

Integrates with your stack; replay history to backfill.

Seeded ≠ verified

Cold-start knowledge is marked and capped, always.

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Honest scope

A diagnosis is an evidence-backed hypothesis for your engineers — not automated remediation. Confidence reflects recorded outcomes; seeded knowledge is labelled distinctly and capped.

FAQ

Common questions

Does Causa see our data?
No — the ingestion contract is structural and payload-free, enforced by schema.
Does it fix things automatically?
No. It recommends; your engineers decide.
What do fix-confidence numbers mean?
How often that fix class verifiably resolved that incident class. Seeded knowledge is capped so it can't inflate confidence.
What does it integrate with?
Anything speaking OpenTelemetry, including common LLM-observability layers.
Next step

Bring your last painful incident.

Built for SRE & on-callAI platform teamsprivacy-sensitive orgs