IFC AI Data Compliance

Map requirements to IFC evidence

AI Data Compliance is about requirement evidence, not generic chat over a model. The inspected workflow imports requirement context such as EIR or DEIR material, reviews mappings to IFC evidence, then runs deterministic assessments against retained model fields and approved mapping data.

Contractual requirements come from the committed requirement register or imported requirement source. The app should not invent requirements, percentages or evidence outside the reviewed inputs.

AI assists, checks decide

Optional AI assistance can help explain reviewer context, but deterministic compliance logic remains authoritative. The implementation explicitly separates fixed assessment math and retained IFC evidence from advisory AI language.

That boundary is important for trust: an AI explanation can make the review easier to read, but it must not change pass, warning or fail outcomes.

Prepare a reviewer package

The workflow supports preparing reviewed results and supported reviewer packages. Use those outputs as evidence for discussion, while keeping professional judgement and project-specific approval routes outside the tool.