BtrLyf is a comprehensive digital platform designed to revolutionize the built environment by facilitating the creation of sustainable buildings through collaboration and AI-driven assessments. Developed by Qi Square, a spin-off from Nanyang Technological University in Singapore, BtrLyf integrates multiple data sources—including open-source information, design data, standards, and user inputs—to generate digital twins of buildings. These digital representations enable stakeholders to perform virtual assessments, analyze building performance, and implement green retrofit measures efficiently. Key Features and Functionality: - Digital Built Environment Mapping: Utilizes GIS-based mapping to provide an overview of buildings within a city, highlighting their sustainability features and potential. - Data Aggregation and Simulation: Combines various data sources to create digital twins, allowing for physics-based simulations and machine-learning analytics to assess and enhance building performance. - Performance Simulation Tools: Offers both automated and manual simulation options to evaluate and optimize energy savings, costs, and return on investment for building improvements. - Collaborative Platform: Connects building owners, facility managers, consultants, technology providers, and financiers, fostering collaboration and data exchange to streamline green building projects. - User Profiles and Dashboards: Enables users to create profiles, manage leads, and share solutions, projects, and events within a global community of over 100,000 sustainability champions. Primary Value and Problem Solved: Buildings account for approximately 40% of global energy consumption and 30% of carbon emissions. Despite the potential to reduce operating costs by 30% to 40% through green retrofit measures, the building industry often lacks the tools to identify and quantify energy-saving opportunities effectively. BtrLyf addresses this challenge by providing a unified digital platform that simplifies data collection, enhances collaboration, and offers AI-powered assessments. This approach eliminates the need for expensive intermediaries, reduces duplication of efforts, and accelerates the adoption of sustainable solutions, ultimately contributing to the decarbonization of the built environment.