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HELIX

AI-powered digital twins of buildings from laser scanning and photogrammetry

Platform that creates accurate 3D digital twins of buildings using LiDAR scanning, photogrammetry, computer vision, and AI. Delivers models in Revit, SketchUp, AutoCAD, and 360° photo formats within days instead of weeks, enabling space planning, asset management, and property optimization.

$125M (via Density acquisition) raisedGrowth Stage
Founded 2019 · Not publicly disclosed (integrated into Density platform); previously used by multiple Fortune 500 real estate portfolio managers
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WHY IT EXISTS

Why This Tool Exists

The Problem

Building teams struggle to create accurate digital documentation of existing facilities. Traditional surveying and CAD modeling take weeks or months, cost $10,000-$50,000 per building, and produce outdated data that doesn't reflect actual building conditions. Real estate managers lack accurate spatial data for lease negotiations, space planning, and facility optimization.

The Solution

Uses aerial drones and ground-based LiDAR scanning combined with photogrammetry and computer vision AI to capture complete building geometry and 360° documentation. Delivers accurate 3D models in industry-standard formats (Revit, SketchUp, AutoCAD) within days for 70-80% cost savings. Integrates with Density's workplace analytics for real-time occupancy and performance data.

USAGE

How You Use It

Delivery Method
SaaSProfessional Services (field scanning)
Integrations
Revit (via Autodesk Design Automation API)SketchUpAutoCADDensity (occupancy analytics)Autodesk Reality Capture (point cloud management)
Disciplines
Architecture, Construction, Facility Management
Workflows
Design & BIM, Operations & Facility Management
Project Phases
Schematic Design, Design Development, Construction Documentation, Operations/FM
Project Types
Commercial, Residential, Healthcare, Mixed-Use
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Building access for scanning, Site survey permission
Optional:Existing CAD models for reference, Historical building documentation
Formats:LAS/LAZ point clouds, JPG/PNG site photos, Drone imagery
Output
What you get
Format:Multi-format digital twin models
Fields:3D Revit models with spaces and properties, 3D SketchUp models for visualization, 2D AutoCAD floor plans, 360° panoramic photo tours, Point cloud data (LAS/LAZ format), Spatial measurement data, Material and fixture documentation
Algorithm
How it works
Model:Proprietary computer vision and AI engine combining LiDAR point cloud processing and photogrammetry
Accuracy:Claims submeter accuracy for building geometry (methodology not publicly detailed); 360° photo documentation captures existing conditions
Privacy
How your data is protected
Retention:Models retained indefinitely in user account; user control over sharing and deletion
Training:Not publicly specified whether production scan data used for model training
Compliance:Integrated into Density compliance (SOC 2 inferred), Enterprise-grade data security (specific certs not publicly disclosed)
API
Integration
Endpoint:Contact vendor for API access via Density platform
Method:REST API (not publicly documented)
USE CASES

Use Cases

  • ·Rapid creation of accurate existing-building digital twins for renovation projects
  • ·Real estate lease negotiation with verified spatial data
  • ·Facility management and asset tracking across building portfolio
  • ·Space utilization analysis combined with occupancy data (via Density)
  • ·Building retrofit planning with accurate as-built geometry
  • ·Multi-building campus documentation and management
PRICING

Pricing

Free
Not available
Pro
Contact vendor for pricing (project-based; varies by building size and complexity)
Enterprise
Custom pricing for portfolio scanning and integration with Density analytics platform
Sources & Research NotesResearch date: 2026-04-04
Data Sources (8)
Fields Checked (14)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, maturityStage, yearFounded, fundingTotal, input-formats, output-fields, algorithm-approach, useCases
Not Found (7)
customerBase-specific-names, pricing-exact-rates, api-documentation, privacy-policy-document, algorithm-accuracy-metrics, compliance-certifications, data-retention-duration
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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