Maket
AI architectural tool that generates detailed floor plans from text descriptions - used by architects, builders, and developers to accelerate space planning.
Maket is an AI-powered architectural design tool that generates residential and commercial floor plan options from a simple text description of the space requirements - specifying number of rooms, square footage, style preferences, and intended use. The AI produces multiple design variations, each with dimensioned layouts, room labels, and structural wall placement that can be used as a starting point for refinement in CAD or BIM tools. Maket is designed for the early exploration phase of architectural projects where speed and breadth of options matters more than construction-document precision. The tool targets architects, real estate developers, interior designers, and homeowners doing pre-construction planning. Founded in 2021 and YC-backed, Maket uses a subscription pricing model starting around $29 per month.
Key Features
- Text-to-floor-plan generation producing multiple design variations from a plain language space description
- Dimensioned layout output with labeled rooms and structural wall placement ready for CAD refinement
- Style and program controls - specify residential vs commercial, number of stories, bedroom count, and square footage targets
- Multiple variation generation from a single prompt allowing rapid exploration of different spatial configurations
- Export to DXF and image formats for importing into AutoCAD, Revit, or BIM workflows as a starting template
- Zoning compliance prompts that factor in basic setback and room adjacency requirements for the selected building type
Use Cases
- Architects generating initial concept floor plan options for client presentations before committing to detailed drawing
- Real estate developers exploring spatial configurations for a new building footprint during pre-feasibility analysis
- Interior designers planning furniture layout and traffic flow from a dimensioned base plan before sourcing pieces
- Homeowners visualizing room configuration options for an addition or renovation before engaging an architect
Pros
- Text-to-floor-plan generation compresses the early schematic exploration phase from days of drafting to minutes
- Multiple variations per prompt supports the iterative client feedback cycle without restarting the drawing each time
- Export to DXF means the AI output integrates into professional CAD workflows rather than remaining a static image
Cons
- Generated plans are concept-level only - not suitable for permit submission or construction documentation without substantial professional refinement
- Complex site constraints like irregular lot shapes or slope cannot be expressed through text prompts alone
- Architectural accuracy varies significantly by building type - residential floor plans are stronger than complex commercial layouts
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