Primary-source citation in AI compliance research
Also known as: AI citation grounding · hallucination-averse AI
An architectural pattern for AI-assisted regulatory research where every answer is grounded in and cites the primary source text — the exact section of a law, standard, or regulation — with no invented citations.
In regulated domains like accessibility law, an AI that hallucinates a citation is worse than useless — it undermines the consultant's professional accountability. Primary-source-citation architecture means the AI retrieves relevant regulation text before generating an answer, and the answer explicitly cites the section it retrieved from.
This is the pattern used by regulation-copilot (Tamar Accessibility's AI product for consulting firms). Every answer to a question about Israeli accessibility law, Israeli Standard 5568, WCAG, or Israeli Standard 1918 cites the exact section or clause — verifiable, not fabricated.