Kernel capabilities implemented. End-to-end platform integration and qualification are progressing.Interactive demonstrationPlatform status

Extended platform

AIOps

Read-only findings over recorded evidence.

Read-only drift, incident, state and summary analysis over audit chains, using deterministic rules. No forecasting, tuning or decision authority.

Demonstrable2 lifecycle positionsNon-production evidence

Responsibility

What AIOps is responsible for

AIOps provides read-only operational understanding: it reads recorded audit evidence and control-plane state and produces drift, incident, state and summary findings using deterministic rules. It cannot admit, permit or dispatch, and it does not forecast or tune policy in the reviewed implementation.

Observability tells you what happened; AIOps is intended to help interpret it. The reviewed implementation reads the same evidence the platform audits and produces deterministic findings without acquiring decision authority.

That separation is a design rule. AIOps cannot admit an action or issue a permit, and a finding from it is not evidence. Forecasting, scenario analysis and policy tuning appear in architectural direction but are not implemented in the reviewed code.

Lifecycle position

Where it sits in the governance lifecycle

Stage numbering is canonical across the site. Open the interactive lifecycle to see every component with responsibilities at each stage.

  1. Evidence and audit

    Keep linked, ordered, reviewable records.

  2. Conformance

    Evaluate outcomes against the original obligations.

Verified capabilities

What is verified today

Capabilities are drawn from the product register. Each one is bounded by the limitations stated further down this page.

  • Read-only drift detection over audit chains
  • Incident, state and summary findings
  • Deterministic rule-based analysis (no model inference)
  • Read-only operational surfaces for operators

Inputs

  • Audit and evidence records
  • Control-plane operational read models

Outputs

  • Drift and incident findings
  • Operational state summaries
  • Read-only explanations

Evidence and maturity

What the evidence supports

Maturity describes verified engineering evidence in a bounded environment. It is not a production-readiness statement.

Demonstrable

Maturity note

A read-only AIOps surface returning real drift, incident, state and summary findings over audit chains was verified live. The analysis is deterministic and rule-based; no forecasting, policy tuning or CP-facing AI is implemented.

Not production-qualified

This label describes verified engineering evidence only. No production deployment, certification, benchmark or customer outcome is claimed.

Evidence recorded

  • Recorded local chain hop 14: read-only drift, incidents, state and summary over audit chains.
  • Live read-only AIOps routes verified in the 2026-11-03 capability audit.

Dependencies

  • Control Plane
  • audit ledger

Dependencies are stated as the product register records them. A dependency is not automatically production-qualified; see its own product or component page for its maturity and limitations.

Limitations

What this product does not do (yet).

Limitations are stated before the evaluation questions so they cannot be missed, downplayed or treated as future-work footnotes.

Limitations — read before evaluating
  • Read-only: cannot admit, permit or dispatch, by design.
  • Deterministic rule-based analysis; no forecasting, policy tuning or CP-facing AI is implemented.
  • A finding is not evidence and must not be treated as authorisation.

No capability on this page should be read as production qualification. If a limitation is material to your use case, it belongs in the evaluation scope — not after it.

Relationship to the platform

How it fits

AIOps is an interpretation layer over the evidence chain. It helps operators understand and tune the system without becoming part of the authority path.

Evaluation questions

  1. Which operational questions should AIOps answer first?
  2. How is AI-generated analysis prevented from becoming authority?
  3. What evidence does an explanation cite?

Next step

Evaluate AIOps against a real control problem.

Bring a system boundary, an action class and a failure mode. The first step is to agree what should be governed and what evidence would count.