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cityweft

AI-generated global 3D city models for architectural site design

Cloud-based platform and API that instantly generates accurate 3D city models with buildings, terrain, infrastructure, and surfaces from global geospatial data sources. Exports to Rhino, SketchUp, Revit, Archicad, Blender or integrates via API for site analysis, master planning, and urban design.

Not publicly specified raisedEarly Stage
Founded 2024 · Not publicly specified (beta phase with university partnerships)
Website → ← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Architects and urban planners manually gather 3D city context data from multiple inconsistent sources (LiDAR surveys, GML datasets, OpenStreetMaps, national mapping agencies) for site analysis and master planning. This manual assembly is time-consuming, inconsistent in quality, and requires specialized GIS expertise. Site design work is delayed waiting for accurate background geometry.

The Solution

AI-powered platform automatically generates high-quality, editable 3D city models with buildings, terrain, infrastructure, and surface textures from global data sources. Models are instantly available for export to standard design tools (Rhino, Revit, Archicad, SketchUp, Blender) or accessible via API for custom integration. Topography accurate to under 1 meter with precise building geometry.

USAGE

How You Use It

Delivery Method
SaaSAPIDesktop Plugin
Integrations
RhinoSketchUpRevitArchicadBlenderGrasshopper
Disciplines
Architecture, Urban Planning
Workflows
Design & BIM
Project Phases
Pre-Design, Schematic Design, Design Development
Project Types
Commercial, Mixed-Use, Residential, Infrastructure, Urban Planning, Masterplan
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Geographic location (latitude/longitude), Area of interest (bounding box)
Optional:Custom data preferences, User account/API key
Formats:Web interface, REST API, Plugin interface
Output
What you get
Format:Editable 3D city models with building, terrain, and infrastructure geometry
Fields:Building models with complex roof geometry, Terrain/topography with elevation data, Urban infrastructure elements, Surface textures and satellite imagery, Metadata for each element
Algorithm
How it works
Model:Proprietary AI data unification engine (specific models not publicly disclosed)
Accuracy:Topography accurate to <1m; building geometry precision not specified
Privacy
How your data is protected
Retention:Not publicly specified
Training:Not publicly specified
Compliance:Not publicly specified
API
Integration
Endpoint:https://cityweft.gitbook.io/docs (API documentation)
Method:REST API
USE CASES

Use Cases

  • ·Rapid site analysis with accurate 3D urban context
  • ·Generative design with parametric access via API and Grasshopper
  • ·Urban masterplanning and massing scenarios
  • ·Competition entries with global 3D city data
  • ·Campus and institutional planning
  • ·Design rendering and visualization with contextual accuracy
  • ·Sustainable design analysis (solar access, wind patterns) using accurate geometry
PRICING

Pricing

Free
Free for students; 1-month free trial for other users
Pro
Pay-per-export starting at €30 per single export; Subscription bundles available for studios and teams
Enterprise
Not publicly specified
Sources & Research NotesResearch date: 2026-04-03
Data Sources (9)
Fields Checked (14)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, algorithm-approach, useCases, pricing, vendor, website
Not Found (13)
total-funding-amount, specific-customer-names, customer-base-count, api-rate-limits, soc2-certification, iso27001, privacy-policy, data-retention-specifics, data-training-practices, enterprise-pricing, webhook-support, algorithm-specific-models, accuracy-percentage
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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