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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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AI Website Builder: An Intelligent Automated Web Development Platform

Authors: Saurabh Dahiya; Ankit Rewar;

AI Website Builder: An Intelligent Automated Web Development Platform

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.

Keywords

Machine Learning, computer science

  • BIP!
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average