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I need a full-stack solution that turns natural-language prompts into production-ready architectural documents. A user will visit the site, type a detailed description of the building they have in mind, specify every key dimension in plain text, press “Generate,” and immediately receive: • A dimension-accurate floor-plan file • A matching elevation model • Downloadable outputs in at least DWG and IFC (plus a browser preview) The engine must work solely from text-based prompts; no uploads or templates will be offered at this stage. Each result has to reach a highly detailed level suitable for permit drawings, with rooms, wall thicknesses, openings, materials and basic MEP placeholders already resolved. The style selector inside the prompt must recognise Modern, Classical and Minimalist vocabulary and reflect it faithfully in the geometry and façade treatment. If a user asks for “a 15 m × 20 m minimalist concrete villa,” the service should respond with the correct footprint, proportional elevations and consistent material palettes. Also the plan pass should be editable by user so minor changes can be made. Backend freedom is yours—stable diffusion–style LLM chains, parametric CAD scripting, or a hybrid pipeline—as long as response times stay under two minutes for a mid-size house and all geometry remains within a 2 mm tolerance of the stated dimensions. Host everything behind a clean React or Vue front end and include a REST endpoint so third parties can integrate the generator. Acceptance criteria • Upload a live URL plus Git repo for code review • Supply a sample prompt library and the resulting DWG/IFC files for QA • Pass an automated test set that checks dimensional accuracy and style compliance I will sign off when the test set passes and the deployment guide lets me replicate the stack on my own AWS account without modification.
Project ID: 40449685
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**Subject:** Proposal: Turning Natural Language into Architectural Plans Hi there, I understand you need a full-stack solution that converts natural-language prompts directly into production-ready architectural outputs. This is a fascinating intersection of NLP, generative design, and practical construction workflows. My background in both full-stack development (React, Node, Python) and AI model fine-tuning (including LLMs and diffusion-based generation) equips me to build exactly this kind of system. I’ve previously delivered similar tools that translate vague user descriptions into structured data (e.g., furniture layouts and floor-plan skeletons), always with a focus on accuracy and downstream usability. My approach would be threefold: first, a clean NLP pipeline that parses prompts (room types, dimensions, style preferences) into structured constraints. Second, a rule-based or learned generation engine that produces building plan components (walls, openings, fixtures) in a standard format like IFC or DXF. Third, a front-end where users can refine the output through further prompts or direct manipulation, closing the loop for production readiness. I’d also ensure the system is modular—so you can swap in your own architectural rules or connect to rendering engines later. I’m confident I can deliver a robust prototype within a short timeline, and I’d love to discuss your specific output requirements (e.g., 2D vs. 3D, target CAD software) to tailor the architecture. Let’s set up a quick call to align on scope and block an initial demo.
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Surat, India
Member since May 17, 2026
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