Explore the challenges of manual PDF to BIM conversion and how AI-powered PDF2BIM reduces geometry setup time by 90% and enables 10x faster Building Energy Modeling workflows.
CCTech celebrates a major achievement as the simulationHub team secures the Second Position at ISV SaaS Fest 2025—an innovation-driven event hosted by AWS and Comprinno. This article showcases how our 2D-to-3D Buildings AI Viewer was engineered using cloud-native, AI-assisted workflows to dramatically accelerate building model generation. From instant geometry creation to scalable AWS integration, the solution demonstrates how CCTech is shaping the future of building energy modeling through intelligent automation and rapid prototyping.
Buildings AI eliminates long-standing interoperability challenges by unifying design files from Revit, AutoCAD, PDFs, and FloorSpaceJS into accurate, simulation-ready building energy models. Through AI-driven automation, PDF2BIM, and seamless BIM integration, it streamlines geometry preparation, reduces errors, and accelerates HVAC load and energy simulation workflows for architects and engineers.
Accurate cooling and heating load estimation is the foundation of energy-efficient HVAC system design. Over the years, ASHRAE has developed and refined various methods for heat load calculations. Each method offers a unique balance between accuracy, complexity, and computational effort.