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TwinMaster

AI copilot-powered digital twin platform for architects

AI-powered digital twin software platform featuring Arch-e, an AI copilot that generates design options enriched with predictive insights on cost, energy, daylight, carbon, and compliance. Reduces planning time by 50% and rework by 30%.

Pricing
$19/month
Alternatives
Nomic AI, Laiout, Leko Labs
Who it's for
Architecture, Structural Engineering, Owner/Developer
$3.1M raisedEarly Stage
Founded 2023 · Undisclosed (beta/early access phase, won BEST INNOVATION at AIA25 Boston conference)
Website → ← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Architects spend weeks iterating on design concepts, manually checking zoning requirements, energy performance, and construction costs. Each design iteration requires separate analysis from different specialists, creating silos and delays. Many promising design alternatives are never explored due to time constraints.

The Solution

Arch-e, a multi-agent AI copilot, acts like a digital design team where specialized agents handle energy, cost, constructability, and compliance analysis in parallel. Architects import 3D models and request design iterations in plain English, receiving instant design options with performance predictions. Design cycles that took weeks now occur in minutes with measurable performance data.

USAGE

How You Use It

Delivery Method
SaaSWeb Application
Integrations
RevitRhinoSketchUp
Disciplines
Architecture, Structural Engineering
Workflows
Coordination & Delivery, Planning & Feasibility
Project Phases
Schematic Design, Design Development, Pre-Design
Project Types
Commercial, Residential, Mixed-Use, Education, Healthcare
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:3D models, Project location context
Optional:Zoning information, Climate data, Project constraints, Design parameters
Formats:Revit models, Rhino files, SketchUp models, IFC, GLTF
Output
What you get
Format:Design options with integrated performance analytics
Fields:Generated 3D design variants, Energy performance estimates, Cost analysis and budget impact, Daylight access predictions, Carbon footprint calculations, Zoning and compliance status, Constructability assessment
Algorithm
How it works
Model:Proprietary multi-agent AI architecture with specialized agents for different design domains (inferred from product description)
Accuracy:Not publicly specified
Privacy
How your data is protected
Retention:Not publicly specified
Training:Not publicly specified
Compliance:Not publicly specified
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Rapid generation and comparison of schematic design concepts with performance data
  • ·Automated compliance checking against zoning regulations and building codes
  • ·Real-time energy and cost impact analysis during design iteration
  • ·Daylight access optimization for commercial and residential projects
  • ·Carbon footprint reduction through design exploration
  • ·Accelerated design development with reduced manual analysis time
  • ·Team-based design collaboration with shared design intelligence
PRICING

Pricing

Free
Free trial available
Pro
$19/month (early bird pricing) for TwinMaster Pro
Enterprise
Contact for enterprise pricing and SSO
Sources & Research NotesResearch date: 2026-02-01
Data Sources (7)
Fields Checked (19)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, fundingTotal, input-required, input-optional, input-formats, output-format, output-fields, control-features, useCases, pricing-free, pricing-pro
Not Found (13)
api-documentation, api-endpoint-details, privacy-policy, privacy-data-retention, privacy-training-data, compliance-certifications, soc2-report, detailed-algorithm-model, accuracy-metrics, named-customers, specific-enterprise-pricing, webhook-support, data-processing-agreements
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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