AI Website Builder: An Intelligent Automated Web Development Platform

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Authors: Saurabh Dahiya, Ankit Rewar
Cited by: 0

Abstract

The increasingpresence hasdemand for rapid digitalamplified the need forefficient, accessible, and automated websitedevelopment tools. Traditional websitecreation requires extensive programmingskills, UI/UX design expertise, backenddevelopment knowledge, and deploymentexperience, making it difficult fornon-technical users to create functional webapplications independently. This researchpresents AI Website Builder, an intelligentautomated web development platformcapable of generating complete, responsivewebsitesdescriptions.using natural-languageThe system leveragesadvancements in Artificial Intelligence andmodern full-stack technologies such asReact, Next.js, Tailwind CSS, Node.js,Prisma ORM, and Neon PostgreSQL.Inaddition, it integrates advanced AI moduladdition, it integrates advanced AImodulesaddition, it integrates advanced AImodulesaddition, it integrates advanced AI moduleslike CodeRabbitrefinement andfor intelligent codeE2B for secure,containerized runtime execution andreal-time previews.The proposed methodology involves promptinterpretation, automated interfacegeneration, dynamic component creation,and code optimization through AI-assistedprocesses. The system also includesmechanisms for project storage, versioncontrol, export functionality, and instantdeployment support. Experimentalevaluation demonstrates that the systemgenerates functional websites with anaverage response time of 5–10 seconds,significantly reducing development time,eliminating repetitive coding tasks, andimproving developer productivity. Theplatform also enhances accessibility forusers with limited technical skills byproviding a seamless, prompt-drivenworkflow.

Fields of Study & Subjects

Mobile and Web Applications Web Applications and Data Management Software Engineering Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 January 2026
Language
EN
Document type
Dataset