Has your automation earned the authority you’ve given it?
Automated controls can execute correctly and still choose poorly or worsen outcomes. Safety Automation assesses judgement and consequences, producing qualified evidence for decisions about authority — including operational automation and cybersecurity response.
Evidence for Automation Governance
Safety Automation provides assurance of automated judgement and outcomes. Capability, judgement and outcome are three assurance questions. Authority is the governance decision made by the accountable owner from the evidence.
Assess One Automated Action
Start with a named control, runbook or agent action. Agree the claim, material outcome, decision rule, observation window and operating and data conditions before testing. Assess judgement, compare credible alternatives where feasible, repeat experiments and report qualified findings with coverage gaps.
The deliverable supports a defined authority rung: observe, recommend, bounded or reversible action, or autonomous action. State the envelope, revocation trigger and fallback. Two runs alone do not establish reliable benefit.
Operational and Cybersecurity Response
Assess retries, restarts, failovers and automated security responses. Examine threat containment, operational harm, adversary adaptation and the consequences of acting or waiting.
Engineering, Technical Assurance and Research
Dynacov delivers engineering and implementation. AIKUS independently challenges technical claims. Safety Automation supplies judgement and outcome evidence for authority decisions.
The first book develops Automation Governance. A second book in development extends the work into automated cybersecurity response. Engagements, clinics and seminars turn these questions into practical evidence.
Certified Assurance Platform
RED HAT CERTIFIED · BUILT FOR OPENSHIFT
Safety Automation is not only a methodology. We built a certified implementation to run controlled assurance experiments inside enterprise OpenShift environments.
The platform creates repeatable conditions, exercises automated controls, captures the resulting evidence and supports counterfactual comparison between automation active and suppressed.
Define the experiment
Fix the claim, material outcome, decision rule, observation window and operating and data conditions before testing.
Exercise the control
Test restart, recovery, failover and related responses under controlled conditions.
Compare and repeat
Compare credible alternatives under matched conditions and repeat runs to assess stability.
Capture the evidence
Record provenance, operational metrics, outcome measures and coverage gaps.
Report a qualified finding
State the supported result and its limits. The accountable owner decides authority, revocation conditions and fallback.
The controls executed as designed. The outcomes got worse.
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OpenShift deployment within agreed permissions and scope
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Controlled experiments in development and staging environments
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Repeatable conditions and traceable evidence records
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Reports state tested conditions, coverage and unresolved questions
We are a RedHat Certified Partner