AI Failure Index · Assessment

AI Recommender failure assessment

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

Recommender failure surface

  • 16failures on this surface
  • 1catastrophic
  • 31%under active regulatory exposure
  1. Brand & Safety Incident

    9 on this surface
    1 Catastrophic 6 High 2 Medium

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

  2. Policy Violation

    6 on this surface
    5 High 1 Medium

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

  3. Data Leakage

    1 on this surface
    1 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.

Where this surface bites hardest

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

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