A significant challenge to the cluster’s co-design approach is integrative data management across all phases of building processes. While this challenge has been targeted from different perspectives, utilizing data models and formats specific to different domains (e.g., building engineering, mechanical and plant engineering), it has not yet been overcome. The models typically represent the flow alongside the process chain and have limited interoperability. A broader view based on data combined from different phases and back-flow of information are not well supported. This project addresses these shortcomings by creating a central data management (CDM) platform that integrates data from multiple phases of the building process, supports co-design based on artificial intelligence (AI) by jointly analyzing these data, and returning data-derived feedback to various parties involved. Having defined the CDM software architecture and implemented a first co-design application in RP9-1, we now focus on data integration algorithms embedded into predictive and adaptive co-design that apply AI methods to prefabrication and on-site construction.