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Digital Blue Foam

AI generative design and spatial analytics platform

Web-based AI platform that combines generative design, spatial analytics, and sustainability insights to accelerate urban planning and building design projects with real-time multi-source data integration.

$2M (founder/friends/family + ongoing funding discussions) raisedGrowth Stage
Founded 2019 · 7,000+ users including Takenaka, Jacobs, AECOM, Emaar Properties, McKinsey
Website →← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Architecture and urban planning teams spend weeks on early-stage feasibility studies, manually analyzing site conditions, regulations, and sustainability metrics across multiple disconnected tools, causing project delays and increased costs.

The Solution

AI-powered platform that automatically analyzes contextual data (climate, regulations, site conditions) and generates optimized building designs in real-time, reducing feasibility study time by 50% and BIM production by 75%.

USAGE

How You Use It

Delivery Method
SaaSDesktop App
Integrations
RevitArchicadRhinoDBF Hub desktop application
Disciplines
Architecture, Civil Engineering, Facility Management
Workflows
Data & Automation, Planning & Feasibility, Operations & Facility Management
Project Phases
Pre-Design, Schematic Design, Design Development
Project Types
Commercial, Residential, Mixed-Use, Infrastructure, Institutional
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Site location/coordinates, Project parameters (building type, area requirements), Design constraints
Optional:BIM models, Project schedules, Sustainability targets, Local regulations
Formats:Geographic coordinates, IFC, RVT, 3DM, Project specification text
Output
What you get
Format:Interactive 3D models with analytics dashboard
Fields:Generated building massing options, Sustainability metrics (carbon emissions, energy performance), Wind and solar analysis data, Feasibility scores and recommendations, Cost estimates, Compliance checks
Algorithm
How it works
Model:Proprietary DBF Engine with LLM integration for urban diagnostics
Accuracy:Claims 15% cost reduction and 50% design acceleration (methodology not published)
Privacy
How your data is protected
Retention:Project-based retention (specific duration not publicly specified)
Training:Not publicly specified
Compliance:CalOPPA compliance, CCPA compliance, Do Not Track honors
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Early-stage feasibility studies for urban development projects
  • ·Automated building massing generation with sustainability optimization
  • ·Multi-scenario analysis for planning approval processes
  • ·Real-time carbon impact assessment during design iterations
  • ·BIM-integrated generative design workflows
  • ·Collaborative design reviews with stakeholder teams
PRICING

Pricing

Free
Trial available (7 days full access)
Pro
Academic/Pro tier - join waiting list for pricing
Enterprise
Custom pricing for 1,000+ person organizations
Sources & Research NotesResearch date: 2026-02-01
Data Sources (7)
Fields Checked (9)
problem, solution, deliveryMethod, integrations, customerBase, fundingTotal, privacy-compliance, core-features, company-background
Not Found (6)
api-documentation, detailed-pricing, specific-algorithm-details, retention-policies, compliance-certifications, training-data-usage
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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