Manual QM provides human judgment, debriefing, and nuance; it is limited by the amount of time available for listening and, therefore, by the sample size. Automated QM applies the same criteria to all conversations, flags interactions for priority review, and highlights discrepancies that a sample alone would not reveal.

In CrossCX, both use the same framework and the same workflows: an organization can start with the manual process, add AI-assisted support for evaluators, and then expand automated evaluation to all or part of its workflows.

For details on how it works, use cases, and results: Automated and AugmentedQuality Monitoring .