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Documentation Index

Fetch the complete documentation index at: https://docs.svrnos.com/llms.txt

Use this file to discover all available pages before exploring further.

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How this works

This page groups documented AI errors by entity (the deployer who shipped the system, or the developer who built the underlying model) and shows which GER codes have fired against each.
  • Counts are the number of distinct errors attributed to each entity, not severity-weighted.
  • GER codes fired lists the codes that appear across that entity’s errors, sorted by frequency.
  • Unknown-attributed entries (unknown-deepfake-technology-developers, generic unknown, unknown-scammers) are excluded — they would dominate the deployer view and aren’t useful as entity-level signals.
Source data comes from the AI Incident Database, used here under attribution. SVRNOS does not host the source records.

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Why this view

The GER classifies governance failure modes, but the same failure mode recurs across very different entities. A per-entity view answers the dual question: what kinds of GER codes has this specific organization triggered? That’s useful for procurement diligence, regulator briefings, and pattern recognition across an organization’s product portfolio. This is a static derivation from public source data — not a SVRNOS judgment about any specific entity’s overall practice. Attribution reflects only what was publicly reported; it is not comprehensive and not adjudicated.