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Hypar

Cloud-based generative design platform for space planning

AI-powered space planning application that converts building requirements into accurate plans and 3D models. Integrates generative algorithms with natural language processing to automate layout generation and optimize spatial arrangements.

$5.5M raised 📈 Growth Stage 💚 Open Source (Open source core with proprietary cloud platform)
Founded 2018 Thousands of users including leading AEC firms (S/L/A/M, Adrianse)

Why This Tool Exists

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The Problem

Architects spend 2-5 hours manually creating space planning layouts from building programs, requiring multiple iterations to balance spatial efficiency with programmatic requirements. Complex projects can take weeks to generate viable test fits.

The Solution

AI-powered platform converts building requirements into accurate floor plans within minutes using generative algorithms. Automatically suggests furniture layouts, tracks space utilization in real-time, and exports directly to Revit for seamless BIM integration.

How You Use It

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Delivery Method

SaaS Plugin
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Integrations

Revit Rhino Excel AutoCAD PDF DXF DWG
Disciplines
Architecture, Facility Management, Owner/Developer
Project Phases
Pre-Design, Schematic Design
Project Types
Commercial, Healthcare, Education, Mixed-Use, Industrial

Data Transparency

Exactly what this tool uses and how

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Input

What it needs

Required: Building program requirements, Space dimensions
Optional: Furniture specifications, Grid layouts, Existing CAD files, Building outlines
Formats: Excel, CSV, DXF, DWG, PDF, PNG, JPG
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Output

What you get

Format: 3D space plans with automated furniture layouts
Fields: Floor plans, Furniture layouts, Space utilization metrics, Area calculations, 3D visualizations
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Algorithm

How it works

Model: Proprietary generative algorithms with ChatGPT integration for natural language processing
Accuracy: Claims optimized spatial efficiency (methodology not published)
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Privacy

How your data is protected

Retention: Project-based retention (duration not specified)
Training: Not publicly specified
Compliance: Enterprise SSO, Authentication configuration
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API

Integration

Endpoint: Platform based on microservices architecture
Method: Python and C# execution environment

Use Cases

  • Healthcare facility space planning and test fits
  • Office and workplace layout optimization
  • Data center space planning and equipment layout
  • Commercial building space allocation and programming
  • Educational facility space planning and furniture layouts

Pricing

Free
Free tier with basic space planning tools
Pro
$25/month with advanced features and conflict detection
Enterprise
Custom pricing with SSO and enterprise features
Website →
📚 Research Sources & Data Quality Last verified: 2026-02-01
Verified Data (10)
problem, solution, deliveryMethod, integrations, pricing, fundingTotal, yearFounded, customerBase, algorithm-approach, open-source-status
Not Found (6)
detailed-privacy-policy, api-documentation, rate-limits, data-retention-specifics, compliance-certifications, algorithm-accuracy-metrics
Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.

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