🔍

aurivus

AI-powered scan-to-BIM conversion

Neural network platform that automatically detects and classifies objects in 3D point clouds from laser scans to accelerate BIM modeling workflows.

$1.02M raised 📈 Growth Stage

Founded 2019 • 2,000+ users in 56 countries (including industrial facilities and buildings)

Website → ← All Tools

Why This Tool Exists

⚠️

The Problem

BIM modelers spend 25-50% of their time manually identifying and tracing objects in point cloud data from building scans, leading to slow project delivery and increased modeling costs. Complex objects like MEP systems are particularly time-consuming to model accurately.

✅

The Solution

Neural network automatically detects and classifies structural elements, MEP systems, architectural features, and furniture in point clouds, then groups object points for direct Revit modeling. Reduces modeling time by 25-50% with AI-powered object recognition.

How You Use It

🚀

Delivery Method

SaaS Plugin

🔌

Integrations

Autodesk Revit E57 export ReCap RCP

Disciplines

Architecture, Structural Engineering, MEP Engineering, Construction

Project Phases

Design Development, Construction Documentation, Construction Administration

Project Types

Commercial, Industrial, Infrastructure, Institutional

Data Transparency

Exactly what this tool uses and how

📥

Input

What it needs

Required: 3D point cloud data

Optional: 2D vector graphics, BIM model for comparison

Formats: E57, ReCap RCP, SLAM scanner data, Terrestrial laser scanner data, LiDAR, iPad Pro/iPhone scanner data

📤

Output

What you get

Format: .aurivus files for Revit plugin and E57 classified point clouds

Fields: Detected object classes, Grouped point clusters by object, Structural elements (walls, floors, roofs), MEP systems (pipes, valves, fittings), Architectural features (windows, doors), Furniture and interior objects

⚙️

Algorithm

How it works

Model: Proprietary neural network trained for building object detection (specific architecture not disclosed)

Accuracy: Claims significant time savings (25-50% modeling time reduction) but specific accuracy metrics not published

🔒

Privacy

How your data is protected

Retention: Personal data retained for contractual obligations, reviewed every 2 years

Training: Not publicly specified whether point cloud data used for AI training

Compliance: GDPR, Swiss Data Protection Act (DSG)

🔌

API

Integration

Endpoint: Contact vendor for API access

Method: Not publicly documented

Use Cases

• Convert building laser scans to Revit BIM models
• Automated MEP system detection and modeling from point clouds
• Industrial facility documentation and reverse engineering
• Structural element identification for renovation projects
• Quality control verification of as-built conditions against design

Pricing

Free

University/student access available

Pro

Contact vendor for pricing

Enterprise

Custom project-based pricing available

Website →

📚 Research Sources & Data Quality Last verified: 2026-02-01

Data Sources (7)

✅

Verified Data (9)

problem, solution, deliveryMethod, integrations, customerBase, yearFounded, fundingTotal, privacy, algorithm-overview

❌

Not Found (5)

detailed-algorithm-specs, accuracy-metrics, specific-api-documentation, detailed-pricing-tiers, point-cloud-training-data-policy

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.