Professional judgment, turned into practical QA systems.

Why Qualidact exists

AI can accelerate learning-content production, but fluent output does not prove instructional alignment, factual support, assessment integrity or release readiness.

Qualidact turns those recurring responsibilities into practical controls, scorecards, worksheets and human review workflows that can be used in day-to-day L&D work.

Design principles

• Quality findings should be evidence-linked and actionable.
• Human accountability comes before automated confidence.
• Detected defects and items requiring verification should be kept separate.
• Critical issues should not disappear inside an average score.
• Recurring QA data should improve production upstream.