ArchiWeb: A web platform for AI-driven early-stage architectural design

Abstract

As society confronts increasingly complex demands and the growing need for carbon-neutral architecture, AI-driven design methodologies are evolving rapidly. However, the lack of a unified integration platform in the design process continues to hinder AI's integration into real-world workflows. To address this challenge, we introduce ArchiWeb, a web-based platform specifically built to support AI-driven processes in early-stage architectural design. ArchiWeb transforms architectural representation and problem formulation by utilizing lightweight data protocols and a modular algorithmic network within an interactive web environment. Through its cloud-native, open-architecture framework, ArchiWeb enables deeper integration of AI technologies while accelerating the accumulation, sharing, and reuse of design knowledge across projects and disciplines. Ultimately, ArchiWeb aims to drive architectural design toward greater intelligence, efficiency, and sustainability—supporting the transition to data-informed, computationally enabled, and environmentally responsible design practices.

Keywords

AI-driven platform / Data protocol / Digital workflow / Algorithmic design / Web based interactivity

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The Author(s). Publishing services by Elsevier B.V. on behalf of Higher Education Press and KeAi.