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CityDigitalTwin

AI-powered urban microclimate and energy simulation platform

Cloud-based platform for architects, urban planners, and municipalities to simulate microclimate, thermal comfort, energy use, and environmental impacts. Enables design teams to test green infrastructure, cool materials, and renewable systems at neighborhood scale before construction.

Pre-Seed/Series A (amount not publicly disclosed) raised Early Stage
Founded 2021 · Beta customers including Philadelphia thermal comfort studies and Riyadh urban energy modeling projects (exact count not disclosed)

Why This Tool Exists

The Problem

Urban planners and architects spend weeks manually analyzing climate impacts on neighborhood designs, relying on spreadsheets and static models. Delayed decision-making and missed sustainability optimization opportunities occur because teams cannot rapidly test design scenarios against urban heat island, wind, and energy variables.

The Solution

CityDigitalTwin enables rapid microclimate and building energy performance simulation in minutes, allowing architects to test design scenarios—including green infrastructure, cool materials, and renewable systems—and make data-informed decisions before construction. GPU-accelerated simulations model urban areas up to 10km x 10km.

How You Use It

Delivery Method
SaaSWeb Application
Integrations
Rhino 3DRevitSketchUp
Disciplines
Architecture, Urban Planning, Sustainability
Project Phases
Schematic Design, Design Development, Pre-Design
Project Types
Urban Development, Mixed-Use, Commercial, Residential, Municipal

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required: Site geometry, Design parameters
Optional: Weather data, Material properties, Vegetation data, Building specifications
Formats: 3D models (Rhino, Revit, SketchUp), Weather files (EPW), GIS data
Output
What you get
Format: Interactive simulation results and comparative analysis dashboards
Fields: Microclimate conditions (temperature, humidity, wind), Outdoor thermal comfort metrics (UTCI), Urban heat island intensity, Building energy consumption estimates, Solar radiation and shading analysis, Scenario comparison visualizations, Vegetation and cool material impact assessments
Algorithm
How it works
Model: Proprietary urban microclimate solver using MultiGPU-CUDA and OpenMP technologies
Accuracy: Validated against field measurements for urban microclimate simulation; accuracy methodology not publicly specified
Privacy
How your data is protected
Retention: Project-based retention (specific duration not publicly specified)
Training: Not publicly specified whether production data used for model training
Compliance: Encrypts data in transit and at rest, Multi-factor authentication available, GDPR-compliant (specific certifications not publicly disclosed), Data breach notification within 72 hours per GDPR
API
Integration
Endpoint: Contact vendor for API access
Method: Not publicly documented

Use Cases

  • · Microclimate and thermal comfort optimization for public spaces and streets
  • · Green infrastructure impact assessment (trees, vegetation, cool roofs, permeable pavements)
  • · Urban heat island mitigation scenario testing and planning
  • · Building energy consumption modeling at neighborhood scale
  • · Design competition entry analysis with climate resilience metrics
  • · Municipal climate adaptation planning and strategy validation

Pricing

Free
1-month free trial access to starter plan
Pro
Pay-per-use: $250 (5 credits), $900 (20 credits), $2,000 (50 credits); Monthly subscriptions: $700 (20 sims/month), $1,200 (40 sims/month), $2,000 (80 sims/month)
Enterprise
Custom pricing for multi-user teams and high-volume simulation needs
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Research Sources & Data Quality Last verified: 2026-04-03
Verified Data (14)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, pricing, control-features, useCases, vendor, website
Not Found (10)
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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.