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Augmenta

Generative AI platform for automated electrical design

Cloud-based platform that automatically generates fully coordinated, code-compliant 3D electrical raceway designs in hours instead of weeks. Uses generative design and AI to optimize routing, eliminate clashes, and minimize material waste.

$29.9M raisedGrowth Stage
Founded 2018 · Miller Electric (ENR Top 500, 40% design time savings documented), C&R Electric, multiple institutional building contractors
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WHY IT EXISTS

Why This Tool Exists

The Problem

Electrical contractors and engineers spend 1.5-2 months per project phase manually designing coordinated 3D electrical systems. Manual routing leads to design clashes, costly redesigns, material waste (15-20%), construction delays, and coordination challenges across disciplines.

The Solution

Generative AI platform (ACP - Augmenta Construction Platform) that automatically creates fully detailed, coordinated, code-compliant (NEC) 3D electrical raceway designs in hours. Revit integration enables seamless workflows. Reduces design time 40-50% and material waste 15-25% per verified case studies.

USAGE

How You Use It

Delivery Method
SaaSCloud
Integrations
Autodesk RevitIFCCloud-based processing
Disciplines
Mep Engineering
Workflows
Data & Automation
Project Phases
Design, Pre-Construction, Detailed Design
Project Types
Commercial, Data Centers, Healthcare, Education, Infrastructure
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:BIM model, Electrical drawings/plans
Optional:Project specifications, Conduit routing preferences, Code compliance rules, Material standards
Formats:Revit files (.rvt), IFC format, DWG drawings
Output
What you get
Format:3D electrical raceway designs with bill of materials and clash detection reports
Fields:3D coordinated conduit routes, Clash detection and conflict reports, Bill of materials with quantities, Material and cost takeoffs, NEC code compliance verification, Design metrics and optimization analysis
Algorithm
How it works
Model:Proprietary generative design engine combining generative design techniques with large-scale AI optimization
Accuracy:Not publicly specified; case studies demonstrate 40-50% design time reduction and 15-25% material waste reduction
Privacy
How your data is protected
Retention:Not publicly specified
Training:Not publicly specified whether production designs used for model training
Compliance:Enterprise-ready architecture claimed, Specific compliance certifications (SOC 2, ISO) not publicly disclosed
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Automated 3D electrical raceway design for large commercial buildings and data centers
  • ·Design time reduction: manual 6-8 week routing completed in hours
  • ·Material waste reduction and cost optimization through algorithmic routing
  • ·National Electrical Code compliance verification and validation
  • ·Design alternative generation and optimization (route variations)
  • ·Clash detection and elimination between electrical and structural/mechanical systems
  • ·Coordination with multi-discipline design teams (MEP integration)
PRICING

Pricing

Free
Contact vendor for demo/trial availability
Pro
Not publicly specified
Enterprise
Not publicly specified; enterprise SaaS model inferred from customer base
Sources & Research NotesResearch date: 2026-04-03
Data Sources (12)
Fields Checked (14)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, customerBase, fundingTotal, vendor, website, useCases
Not Found (7)
pricing-plans, api-documentation, privacy-policy, data-retention-policy, compliance-certifications, algorithm-accuracy-methodology, training-data-sources
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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