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Residential Floor Planning with Generative AI

We developed an intelligent chat-based design system that generates residential floor plans directly from natural language input.
Users can simply describe their requirements  like “3 BHK with open kitchen and balcony” and the AI instantly produces a functional, editable layout.

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Summary :

We have built a conversational AI tool that transforms user prompts into fully generated architectural floor plans.
The system combines generative design and computer vision techniques to understand room requirements, optimize layout flow, and render the plan visually.
Users can refine designs interactively through chat commands or the editing interface, making early-stage planning faster, smarter, and accessible for everyone.

Problem

Problem

Objectives

  • Enable Conversational Design

    Allow users to generate complete floor plans using text prompts.

  • Simplify Design Revisions

    Support modifications through chat or drag-and-drop UI.

  • Save Design Time

    Automate initial layout creation and iteration.

  • Support Civil Planners & Clients

    Make architectural design accessible to non-designers.

  • Enhance Visualization

    Instantly display layout previews for quick decision-making.

Challenges

  • Interpreting natural language descriptions into spatial layouts accurately.
  • Balancing design aesthetics with functional constraints.
  • Maintaining proportional accuracy between rooms and dimensions.
  • Handling multi-turn chat updates without losing layout context.
  • Rendering real-time updates seamlessly in the UI.

Solution

  • Designed a chatbot-driven floor plan generation system that translates user requirements into structured spatial layouts.
  • Integrated generative design models to allocate space dynamically for bedrooms, kitchens, and living areas.
  • Used natural language understanding (NLU) to interpret prompts like “add a balcony” or “move the kitchen to the left.”
  • Developed a visual interface where users can edit the plan directly or refine it through conversational input.
  • Implemented real-time rendering of layout updates to reflect every change instantly.
  • Delivered a fast, interactive design assistant that helps planners, architects, and clients co-create designs intuitively.

Architecture

Prompt Input
User enters room and layout requirements through chatbot.
Understanding Layer
NLU model interprets the intent and spatial relationships.
Design Generation
Generative engine creates a structured 2D floor plan.
Interactive Editing
Users modify the layout via chat or drag-and-drop UI.
Visualization Output
Updated floor plan is rendered instantly for review.

Results & Impact

Automated floor plan generation from simple text input

Enabled interactive, conversational design experience

Reduced concept design time from hours to minutes

Delivered editable visual interface for instant plan updates

Made civil planning accessible to non-technical users and early-stage clients

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Santiago Correal Mantilla
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Brainy Neurals is an incredibly skilled and adaptable team. Whether I come with a full plan or just a vision, they always deliver beyond expectations.
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My experience with this project showcased the team’s strong expertise in computer vision and depth estimation. They provided a complete solution, including the app and backend, ensuring seamless integration and high performance.
Billy Brush
Billy Brush
Founder, Darkhorse.AI
The team's attention to detail in data annotation was evident throughout the project. They provided accurately labeled datasets with consistency, ensuring smooth AI model training. Their structured approach made the entire process efficient and reliable.
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