AI Failure Index · Assessment

AI Algorithmic Decision failure assessment

The failure modes that hit Algorithmic Decision systems in production, the real indexed incidents behind each, and the runtime control that would have caught them.

Algorithmic Decision failure surface

  • 69failures on this surface
  • 3catastrophic
  • 41%under active regulatory exposure
  1. Policy Violation

    36 on this surface
    1 Catastrophic 28 High 6 Medium 1 Low

    Runtime control OmniGuard authors policy at the runtime layer and enforces it inline. Prism reads the model's intent against the policy boundary.

  2. Brand & Safety Incident

    16 on this surface
    2 Catastrophic 10 High 4 Medium

    Runtime control Prism reads the model's representation against brand and safety policy. OmniGuard blocks inline. AIDR provides the post-incident audit trail.

  3. Agentic Action Error

    10 on this surface
    7 High 3 Medium

    Runtime control AgentRealm is purpose-built for this. The agent-runtime layer above Prism and OmniGuard inspects each tool call against intent and scope, and intervenes before the action commits.

  4. Hallucination

    4 on this surface
    2 High 2 Medium

    Runtime control Prism observes hallucination signatures in the model's internal state. AIDR flags the moment the model commits to a fabricated claim. OmniGuard can block the response inline.

  5. Data Leakage

    2 on this surface
    2 High

    Runtime control OmniGuard redacts inline. Prism observes the model's representations to flag identity-bound content before it reaches a response. AIDR provides the audit trail.

  6. Identity & Access Drift

    1 on this surface
    1 Low

    Runtime control OmniGuard enforces identity-bound scope at every tool call. AgentRealm reconciles agent action with the assigned principal in real time.

See how Realm catches these failure modes at runtime, before they reach a user.

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