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Field guide

AI hallucinations are an architecture problem

Why models answer from nowhere, what an ungrounded answer costs a regulated team, and the five design choices that stop one from reaching the reader. The five choices double as an evaluation checklist for any AI knowledge tool.

What's inside

AI Hallucinations Guide

  • A plain definition of hallucination, and why a better model won't fix it
  • Three reasons a model produces sentences with no source behind them
  • Four costs a regulated team carries when an answer cannot be proved
  • A warning about the vendor who promises zero hallucinations
  • Five design choices that keep an unsourced sentence out of an answer
  • One question that separates a vendor's prompt from a vendor's architecture

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What this looks like in Sovrinty

Sovrinty carries a citation on every answer, traceable to an approved source and version, and removes unsourced sentences before serving. That is architecture, not a prompt: ranking and confidence are computed separately, so popularity cannot manufacture certainty. If it can't cite it, it won't say it.

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