Key features

Check the quality of a digital twin through schema and data validation

Check geometry clashes between design categories in a digital twin

Perform advanced logical checks and detect inconsistencies through machine learning enabled validation

Define suppression rules for clash detection based on classifications or categories

Validate digital twin data

Set up validation rules to ensure correct classification and availability of data in a digital twin. Logically group validation rules into tests and auto-trigger validation tests as new data is introduced to the digital twin.

Detect geometry clashes

Perform clash detection between different disciplines and between different design categories, along with the ability to define schema-based suppression rules. The clash engine also supports features like overlap calculation, surface touching suppression, and reference hierarchy inclusion.