Implement safeguards or technical controls to prevent hallucinated outputs
Screenshot of code or configuration showing groundedness validation - may include filters checking responses against source documents, fact-checking API integration, or logic comparing generated content to retrieved context for factual accuracy.
Screenshot of UI or output format showing citations and source attributions provided to users - may include inline citations, source links, reference lists, or attribution labels identifying where information originated.
Screenshot of UI or output format showing confidence levels, uncertainty disclaimers, or warnings for generated information - may include confidence score displays, low-certainty warnings, or standard disclaimers about potential inaccuracies.
Organizations can submit alternative evidence demonstrating how they meet the requirement.

"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."

"Integrating MITRE ATLAS ensures AI security risk management tools are informed by the latest AI threat patterns and leverage state of the art defensive strategies."

"Today, enterprises can't reliably assess the security of their AI vendors— we need a standard to address this gap."

"Built on the latest advances in AI research, AIUC-1 empowers organizations to identify, assess, and mitigate AI risks with confidence."

"AIUC-1 standardizes how AI is adopted. That's powerful."

"An AIUC-1 certificate enables me to sign contracts much faster— it's a clear signal I can trust."