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AIOps SIA · cana.si

Detect, diagnose and self-heal.

A super-intelligent SRE that watches every signal across your stack. The AIOps SIA cuts alert noise, predicts failures before they happen, finds root cause in minutes and runs pre-approved remediations — then writes the postmortem.

aiops-sia · checkout-api · p99 latency
● anomaly · +412% p99 at 14:02cause: deploy #8812 · conn pool 10→4✓ rolled back · verified 14:06postmortem drafted · PM-311

67%

Of organizations lose more than $300,000 per hour of downtime

Industry benchmark cited by Delos (2026)

40–60%

MTTR reduction reported across enterprise AIOps deployments

Delos, AIOps benchmarks (2026)

80–90%

Alert volume reduction from event correlation

Delos, AIOps benchmarks (2026)

What it owns

Reliability: from the first anomaly to the closed postmortem, across infrastructure, applications and cloud spend.

The agent roster

Signal Correlator

Merges duplicate and cascading alerts from every tool into one incident with context.

Anomaly Hunter

Learns normal behavior per service and flags deviations without static thresholds.

Forecaster

Spots early degradation and warns hours ahead of failure or capacity exhaustion.

Root Cause Analyst

Correlates logs, metrics, traces and recent changes to name the likely cause.

Remediator

Selects a pre-approved runbook step, executes it, and verifies the fix.

Change Risk Scorer

Scores deploys and config changes for risk before they ship.

FinOps Analyst

Finds idle, oversized and orphaned cloud resources and opens savings PRs.

Scribe

Writes timelines, postmortems and prevention tickets automatically.

Use cases

What the AIOps SIA does from day one.

01

Alert noise reduction

Ingest alerts from every monitor and collapse storms into a handful of actionable incidents, with ownership and blast radius attached.

On-call engineers see signal, not noise.

Signal Correlator
02

Predictive failure warning

Detect slow-burn degradation — memory leaks, disk fill, queue growth — and warn before customers are affected.

Fix it before it breaks.

ForecasterAnomaly Hunter
03

Automated root cause analysis

Walk the service graph, compare against recent deploys and config changes, and present the likely cause with evidence.

Root cause in minutes, not war rooms.

Root Cause Analyst
04

Self-healing remediation

Restart, scale, fail over or roll back using pre-approved runbooks — with verification and automatic escalation if the fix doesn't hold.

Remediator
05

Change risk intelligence

Score every deploy for risk using blast radius, test coverage and history; hold risky changes for review.

Change Risk Scorer
06

Cloud cost optimization

Continuously right-size, schedule and clean up cloud resources — and open the infrastructure-as-code PR for approval.

Savings that compound monthly.

FinOps Analyst
07

Capacity planning

Forecast compute, storage and GPU needs from growth trends and planned launches.

Forecaster
08

Postmortems on autopilot

Timeline, contributing factors, customer impact and prevention items — drafted before the incident channel goes quiet.

Scribe
How it works

A closed loop, not a one-shot answer.

  1. 01

    Ingest

    Metrics, logs, traces, events, deploys and tickets from your observability stack.

  2. 02

    Correlate

    Deduplicate, group and enrich with topology and ownership.

  3. 03

    Diagnose

    Rank likely causes with evidence and confidence.

  4. 04

    Remediate

    Run approved runbooks; verify; escalate when needed.

  5. 05

    Learn

    Postmortem, prevention tickets, and better runbooks next time.

Earned autonomy

Four modes. One dial per use case.

1

Observe

Reads signals and builds understanding. No actions.

2

Recommend

Proposes actions with evidence for a human to take.

3

Act with approval

Executes once a human approves, by risk tier.

4

Autonomous

Acts within policy, announces and logs everything.

Autonomy is set per use case and expands only when evaluations against your own historical data prove it is ready.

Guardrails

Governed by default, auditable always.

  • Remediations limited to pre-approved runbooks per service
  • Blast-radius limits and change freezes respected
  • Every action verified, logged and reversible
  • Human escalation when confidence is low

Connects to

The systems you already run.

DatadogPrometheusGrafanaSplunkElasticNew RelicDynatracePagerDutyOpsgenieServiceNowKubernetesAWSAzureGoogle CloudTerraform

Connections are delivered through Cana MCP adapters. Availability varies by deployment; product names are trademarks of their owners.

Design goals

What we build the AIOps SIA to deliver.

−60%

Mean time to resolve

−90%

Alert noise

Minutes

To root cause

Design goals, not guarantees. Results depend on data, systems and the autonomy level you choose.

FAQ

Questions, answered.

Do we need to replace our monitoring tools?

No. The AIOps SIA sits on top of the tools you already use and connects to them through MCP.

Will it take actions without us knowing?

Only the actions you pre-approve, on the services you choose. Every action is announced in your incident channel and logged.

How long until it's useful?

Alert correlation and RCA work from day one on historical data. Self-healing is switched on runbook by runbook as you build trust.

Put the AIOps SIA to work. Get early access.

Join the waitlist for early access to Super Intelligent Agents and updates as Cana opens up.