AI Construction Plan Generator
Budget: $250 – $750 USD
I need a production-ready AI application that ingests a user-supplied 2D floor plan (PDF, PNG, or DWG) plus any accompanying building-section notes, then automatically produces a full, permit-ready drawing set.
Core output must include:
• Foundation plan
• Floor-framing plan
• Building sections
• Roof-framing plan
• Exterior elevations
The engine has to read the project’s geographic location, look up the corresponding climate and loading data, and embed all mandatory IRC 2018 clauses directly into the sheets (live references, snow/wind loads, footing depths, insulation R-values, etc.). Because the target audience is professional builders and code officials, the drawings must hit an advanced level of detail: framing member sizing, schedules, dimension strings, call-outs, legends, title blocks, and a basic material take-off table.
Typical flow I envision
1. User uploads the 2D floor plan and enters site ZIP/postcode.
2. AI parses geometry with computer-vision (OpenCV or similar) and converts it to a clean parametric model.
3. Generative rules (Python, TensorFlow/Keras, or your preferred stack) combine the parsed model with rule-based logic that encodes IRC 2018.
4. Finished sheets are pushed to a CAD/BIM file (DWG, DXF, or RVT) and a collated PDF set.
Acceptance criteria
• All five plan types render without manual post-processing.
• Each sheet carries correct IRC 2018 citations and site-specific loads.
• Output passes an automated clash-check and basic span/verifier script.
• The system exports within 60 seconds for an average 2,500 sq ft house.
If you have experience with CAD APIs (AutoCAD, Revit, IFC), machine-vision parsing, and rule-based code compliance, I’d love to see your proposed approach and timeline.
Core output must include:
• Foundation plan
• Floor-framing plan
• Building sections
• Roof-framing plan
• Exterior elevations
The engine has to read the project’s geographic location, look up the corresponding climate and loading data, and embed all mandatory IRC 2018 clauses directly into the sheets (live references, snow/wind loads, footing depths, insulation R-values, etc.). Because the target audience is professional builders and code officials, the drawings must hit an advanced level of detail: framing member sizing, schedules, dimension strings, call-outs, legends, title blocks, and a basic material take-off table.
Typical flow I envision
1. User uploads the 2D floor plan and enters site ZIP/postcode.
2. AI parses geometry with computer-vision (OpenCV or similar) and converts it to a clean parametric model.
3. Generative rules (Python, TensorFlow/Keras, or your preferred stack) combine the parsed model with rule-based logic that encodes IRC 2018.
4. Finished sheets are pushed to a CAD/BIM file (DWG, DXF, or RVT) and a collated PDF set.
Acceptance criteria
• All five plan types render without manual post-processing.
• Each sheet carries correct IRC 2018 citations and site-specific loads.
• Output passes an automated clash-check and basic span/verifier script.
• The system exports within 60 seconds for an average 2,500 sq ft house.
If you have experience with CAD APIs (AutoCAD, Revit, IFC), machine-vision parsing, and rule-based code compliance, I’d love to see your proposed approach and timeline.
Related categories:
Python
CAD/CAM
Building Architecture
AutoCAD
Machine Learning (ML)
3D Modelling
Keras
Computer Vision