TAVRICONTACT
Technology / Failover governance

AI Failover.
Continuity with control.

Governed transition of decision responsibility between AI systems when integrity, reliability, or operating conditions degrade, designed for regulated and safety-critical environments.

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Core concept

Availability is not enough.

An AI system can remain online while output quality degrades. The system must govern which pathway is permitted to act, not merely keep compute running.

01 / Definition

What AI failover means

AI failover is the managed transition of decision responsibility between AI systems when performance, reliability, or operating conditions change. Unlike infrastructure failover, the objective is not only continuity. It is maintaining trustworthy operation where outputs can affect real-world systems.

Validation methods such as shadow execution, replay, canary, and hybrid approaches generate evidence. Governance then uses that evidence to determine whether authority may change.

02 / Control layer

Governed at every transition.

01 / AuthorityAuthority governance

Separate validation from operational control. Authority transitions are explicit, governed, and observable.

02 / OversightContinuous oversight

Monitor behavior under real operating conditions using multiple signals to support informed governance decisions.

03 / DegradationTriggered governance

Constrain authority and govern transitions using validation thresholds before degraded outcomes are allowed to act.

04 / EvidenceAudit readiness

Maintain reviewable records of triggers, authority changes, and operating context with integrity protections.

03 / Operational risk

Why traditional failover is insufficient

  • Silent degradation: systems may appear healthy while output quality drifts over time.
  • Operational exposure: incorrect decisions may create physical, financial, or regulatory risk.
  • Restart dependence: recovery cannot rely only on restarts or downtime-based restoration.
  • Unclear handoff: a backup path is not safe unless its authority is validated, assigned, and reviewable.

The technology is part of Tavri's protected architecture for controlled governance of inference authority.

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