Higharc Research: BIM-Native Tokenization for Constraint-Aware Room Layout Synthesis

See how Higharc is bringing AI-assisted room layout generation into Higharc Studio with Data-Driven Entity Prediction (DDEP). In this demo, Manuel Rodríguez Ladron de Guevara from Higharc's Special Projects team introduces an interactive layout generation workflow inspired by Cursor's code autocomplete experience. Read the blog: https://hubs.li/Q04CSrSn0 As architects and drafters work in Studio, DDEP automatically predicts furniture, fixtures and other room elements based on the room's geometry and type. Suggestions appear as live, ghosted previews that users can accept with the Tab key or explore through alternative arrangements. The demonstration shows how home designers can: Preview AI-generated room layouts before accepting them Add predicted furniture and fixtures using the Tab key Cycle through alternative furniture arrangements and sizes Generate layouts for multiple room types, including kitchens, bathrooms, living spaces and garages Automatically receive updated layout suggestions when room dimensions or existing elements change The result is a more interactive approach to AI-assisted home design, where designers can evaluate and refine spatial layouts directly within their workflow. The technology builds on Higharc's research into BIM-native spatial AI and constraint-aware room layout generation. Explore the research: https://manuelladron.github.io/sbm/ #HomebuildingAI #GenerativeDesign #BIM #SpatialAI #Higharc #BuildersChoice #Homebuilding