High-Accuracy Text-to-CAD/CAM/CAE Generation Using Generative AI: The Archgen Framework

High-Accuracy Text-to-CAD/CAM/CAE Generation Using Generative AI: The Archgen Framework | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article High-Accuracy Text-to-CAD/CAM/CAE Generation Using Generative AI: The Archgen Framework Manish negi, Shivam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8633983/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We introduce ArchGen, a state-of-the-art Text-to-CAD framework capable of generating complex, parametric 3D architectural and structural models directly from natural language prompts. Unlike conventional text-to-CAD systems that often struggle with design complete- ness and structural accuracy, ArchGen employs a multi-stage orchestration pipeline including prompt validation, CAD generation, execution checks, iterative refinement, and quality assess- ment. Leveraging retrieval-augmented generation with caching and cross-stage insight sharing, the system consistently produces highly detailed models, such as multi-story buildings, struc- tural reinforcements, and layout-precise assemblies. The outputs demonstrate architectural re- alism, supporting repetitive elements like floors, grids, and reinforcement details, making them directly usable for professional prototyping and design visualization. Experimental evaluation confirms that ArchGen achieves superior validity, geometric consistency, and requirement ful- fillment compared to baseline approaches. By bridging natural language understanding with intelligent design automation, ArchGen sets a new benchmark for CAD generation, accelerating workflows in architecture, structural engineering, and industrial design. Artificial Intelligence and Machine Learning Text-to-CAD parametric Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8633983","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":576440336,"identity":"cad42b9d-b669-4e9d-bad3-d7accc39bc48","order_by":0,"name":"Manish negi","email":"","orcid":"","institution":"Delhi technological 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Framework\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"archigen ai labs private limited","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":" Text-to-CAD parametric ","lastPublishedDoi":"10.21203/rs.3.rs-8633983/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8633983/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe introduce ArchGen, a state-of-the-art Text-to-CAD framework capable of generating complex, parametric 3D architectural and structural models directly from natural language prompts. Unlike conventional text-to-CAD systems that often struggle with design complete- ness and structural accuracy, ArchGen employs a multi-stage orchestration pipeline including prompt validation, CAD generation, execution checks, iterative refinement, and quality assess- ment. Leveraging retrieval-augmented generation with caching and cross-stage insight sharing, the system consistently produces highly detailed models, such as multi-story buildings, struc- tural reinforcements, and layout-precise assemblies. The outputs demonstrate architectural re- alism, supporting repetitive elements like floors, grids, and reinforcement details, making them directly usable for professional prototyping and design visualization. Experimental evaluation confirms that ArchGen achieves superior validity, geometric consistency, and requirement ful- fillment compared to baseline approaches. By bridging natural language understanding with intelligent design automation, ArchGen sets a new benchmark for CAD generation, accelerating workflows in architecture, structural engineering, and industrial design.\u003c/p\u003e","manuscriptTitle":"High-Accuracy Text-to-CAD/CAM/CAE Generation Using\n\nGenerative AI: The Archgen Framework","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 05:31:36","doi":"10.21203/rs.3.rs-8633983/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"984da0e7-f355-4d0c-b912-799566ce646a","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61328728,"name":"Artificial Intelligence and Machine Learning"}],"tags":[],"updatedAt":"2026-01-20T05:31:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-20 05:31:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8633983","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8633983","identity":"rs-8633983","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}